Tag: Model Answer

  • [Solved] WK1 DISCUSSION B HP-213

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    COMPLETE WORK IN DETAIL 250 WORDS – ## WK1DISCUSSIONBHP-213.odt **## WK1DISCUSSIONBHP-213.odt** ## Thumbnails/thumbnail.png You have learned about the two indexes in the CPT code set from the chapter readings. These are the Alphabetic Index and the Tabular index. The Alphabetic Index can be located …

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    COMPLETE WORK IN DETAIL 250 WORDS

    – ## WK1DISCUSSIONBHP-213.odt

    **## WK1DISCUSSIONBHP-213.odt**

    ## Thumbnails/thumbnail.png

    You have learned about the two indexes in the CPT code set from the chapter readings. These are the Alphabetic Index and the Tabular index. The Alphabetic Index can be located at the end of the CPT manual. This is set up similar to a medical dictionary and has main terms that are in bold as well as sub-terms which include a code or code range that we would use to start the code selection process. From there we would refer to the Tabular index which is one of the six main sections of the CPT manual to look up the full description of the CPT code we found in the Alphabetic index. This is the two-step process needed when looking up our CPT codes.

    ###### Illustrate your current knowledge by accurately using the CPT indexes.

    Include the following aspects in the discussion:

    – Select a term and code from the Alphabetic index, and then find this same code in the Tabular index.

    – Think back to the last time you or a loved one went to a physician. Share a code with the full description of the procedure or service represented that was performed.

    – Reflect on and share why you choose this code and your overall experience on the code selection process.

    – Discuss if you felt this was an easy process to navigate or did you experience any challenges in the process of using both indexes?

    250 WORDS IN DETAIL

    **## WK1DISCUSSIONBHP-213.odt**

    ## Thumbnails/thumbnail.png

    You have learned about the two indexes in the CPT code set from the chapter readings. These are the Alphabetic Index and the Tabular index. The Alphabetic Index can be located at the end of the CPT manual. This is set up similar to a medical dictionary and has main terms that are in bold as well as sub-terms which include a code or code range that we would use to start the code selection process. From there we would refer to the Tabular index which is one of the six main sections of the CPT manual to look up the full description of the CPT code we found in the Alphabetic index. This is the two-step process needed when looking up our CPT codes.

    ###### Illustrate your current knowledge by accurately using the CPT indexes.

    Include the following aspects in the discussion:

    – Select a term and code from the Alphabetic index, and then find this same code in the Tabular index.

    – Think back to the last time you or a loved one went to a physician. Share a code with the full description of the procedure or service represented that was performed.

    – Reflect on and share why you choose this code and your overall experience on the code selection process.

    – Discuss if you felt this was an easy process to navigate or did you experience any challenges in the process of using both indexes?

    250 WORDS IN DETAIL

  • [Solved] Tiff week 6

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    In-depth study guidance and analytical solution covering Tiff week 6.

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    Full assignment prompt and step-by-step guidance are included in the downloadable solution file.

  • [Solved] WK1 ASSIGNMENT HP-213

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    COMPLETE WORK IN DETAIL – ## WK1ASSIGNMENTHP-213.odt **## WK1ASSIGNMENTHP-213.odt** ## Thumbnails/thumbnail.png ##### A Typical Day as a Medical Coder and Biller Essay As a medical coder, you will be responsible for reviewing patient documentation for encounters that has been added to an Electronic …

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    COMPLETE WORK IN DETAIL

    – ## WK1ASSIGNMENTHP-213.odt

    **## WK1ASSIGNMENTHP-213.odt**

    ## Thumbnails/thumbnail.png

    ##### A Typical Day as a Medical Coder and Biller Essay

    As a medical coder, you will be responsible for reviewing patient documentation for encounters that has been added to an Electronic Health Record by a provider. You will ensure the accuracy and integrity of the codes that are used. Additionally, you will review each medical record for compliance purposes and report issues that may be apparent. When there is a question, you will ask or query your provider to confirm that the medical record supports the code selection. It really begins with the medical coder as they are the gatekeepers or coding accuracy and compliance.

    Explore aspects of a coding position.

    Include the following aspects in the assignment:

    –  Describe what you feel a day may be like once you become a coder

    –  What do you think will be most challenging?

    –  Summarize why it is essential to collaborate with clinical staff (MDs/APRNs) to resolve coding questions/discrepancies

    –  Provide an example of a time when it may be necessary to query a physician.

    COMPLETE IN DETAIL

    **## WK1ASSIGNMENTHP-213.odt**

    ## Thumbnails/thumbnail.png

    ##### A Typical Day as a Medical Coder and Biller Essay

    As a medical coder, you will be responsible for reviewing patient documentation for encounters that has been added to an Electronic Health Record by a provider. You will ensure the accuracy and integrity of the codes that are used. Additionally, you will review each medical record for compliance purposes and report issues that may be apparent. When there is a question, you will ask or query your provider to confirm that the medical record supports the code selection. It really begins with the medical coder as they are the gatekeepers or coding accuracy and compliance.

    Explore aspects of a coding position.

    Include the following aspects in the assignment:

    –  Describe what you feel a day may be like once you become a coder

    –  What do you think will be most challenging?

    –  Summarize why it is essential to collaborate with clinical staff (MDs/APRNs) to resolve coding questions/discrepancies

    –  Provide an example of a time when it may be necessary to query a physician.

    COMPLETE IN DETAIL

  • [Solved] Pharm week 6 Reply to Peer 1

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    **Week 6 Discussion: Patient With Polydipsia and Weight Gain** **Nonpharmacologic Treatments Recommended to FM** Given FM's diagnosis of new-onset type 2 diabetes mellitus (T2DM), lifestyle modifications are critical. The following nonpharmacologic strategies are recommended: – **Medical nutrition t…

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    **Week 6 Discussion: Patient With Polydipsia and Weight Gain**
    **Nonpharmacologic Treatments Recommended to FM**
    Given FM's diagnosis of new-onset type 2 diabetes mellitus (T2DM), lifestyle modifications are critical. The following nonpharmacologic strategies are recommended:
    – **Medical nutrition therapy (MNT):** A referral to a registered dietitian is recommended to develop a meal plan that supports weight loss and glycemic control. FM should be educated on carbohydrate counting and choosing low-glycemic index foods (American Diabetes Association [ADA], 2024).
    – **Physical activity:** FM should engage in at least 150 minutes per week of moderate-intensity aerobic activity and strength training twice weekly, as tolerated (ADA, 2024).
    – **Behavioral counseling:** Counseling or behavioral therapy is advised to address emotional eating and mental health, especially in light of FM’s reported loneliness and depression during the pandemic.
    – **Self-monitoring:** FM should be educated on how to monitor his blood glucose at home, given his elevated A1c and random glucose levels.
    **Pharmacologic Treatments Recommended or Avoided**
    Due to FM's significant hyperglycemia (random glucose of 358 mg/dL and A1c of 11.4%), pharmacologic therapy is indicated.
    – **Recommended:**
    – **Metformin** is the first-line pharmacologic agent unless contraindicated. It enhances insulin sensitivity and has a favorable weight profile (ADA, 2024).
    – **GLP-1 receptor agonists** (e.g., semaglutide) or **SGLT2 inhibitors** (e.g., empagliflozin) may be added for further glycemic control, weight reduction, and cardiovascular benefit. These classes are advantageous for patients with obesity and elevated cardiovascular risk (Davies et al., 2022).
    – **Avoided:**
    – **Sulfonylureas** and **insulin** may promote weight gain and hypoglycemia and may not be ideal as initial treatments unless FM is experiencing severe hyperglycemia symptoms.
    – **Thiazide diuretics** (e.g., hydrochlorothiazide) can worsen glycemic control. Switching to a more metabolically favorable antihypertensive should be considered (ADA, 2024).
    **Additional Laboratory Tests Recommended**
    – **Fasting lipid panel:** To assess cardiovascular risk and guide statin therapy.
    – **Serum creatinine and estimated glomerular filtration rate (eGFR):** To evaluate renal function before initiating metformin or SGLT2 inhibitors.
    – **Liver function tests:** Baseline testing is necessary prior to initiating some antidiabetic agents.
    – **Urine albumin-to-creatinine ratio (UACR):** To screen for diabetic nephropathy.
    – **Thyroid-stimulating hormone (TSH):** To rule out thyroid dysfunction, which can impact weight and glycemic control.
    **References**
    American Diabetes Association. (2024). _Standards of care in diabetes—2024_. _Diabetes Care, 47_(Supplement 1), S1–S200. [https://doi.org/10.2337/dc24-S001](https://doi.org/10.2337/dc24-S001)
    Davies, M. J., Aroda, V. R., Collins, B. S., Gabbay, R. A., Green, J., Maruthur, N. M., … & Wexler, D. J. (2022). Management of hyperglycemia in type 2 diabetes, 2022: A consensus report by the ADA and the European Association for the Study of Diabetes (EASD). _Diabetes Care, 45_(11), 2753–2786. [https://doi.org/10.2337/dci22-0034](https://doi.org/10.2337/dci22-0034)

  • [Solved] WEEK 6

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    For this week's discussion, you will take a closer look at findings from your population health assessment & prevention project. 1. Identify the role of your collaborating healthcare professional and share a needed change the two of you identified in your assessment. 2. Identify a community stakehol…

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    For this week's discussion, you will take a closer look at findings from your population health assessment & prevention project.
    1. Identify the role of your collaborating healthcare professional and share a needed change the two of you identified in your assessment.
    2. Identify a community stakeholder or policy maker that could support the recommended change. What resources might be needed?
    3. Provide a paragraph that discusses your advocacy for this change process and how your identified stakeholder or policymaker could help you achieve the recommended change.

  • [Solved] WEEK 6 RE

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    #1 In the assessment, I worked with Bernadette Alamillo, a Registered Nurse, who has lived in Piru all her life. She gave valuable information on the healthcare issues seniors face in the community. Through her help, it was discovered that many seniors in Piru struggle with chronic diseases because …

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    #1
    In the assessment, I worked with Bernadette Alamillo, a Registered Nurse, who has lived in Piru all her life. She gave valuable information on the healthcare issues seniors face in the community. Through her help, it was discovered that many seniors in Piru struggle with chronic diseases because they do not have enough access to care facilities or transportation. While assessing the situation, we agreed that having reliable transportation for seniors would guarantee they could make all their medical appointments. She explained that when transportation is lacking, people often miss their medical appointments, their health worsens, and they end up in the hospital more often. Because of this, we worked together to diagnose the community’s main healthcare problem and suggest mobile clinics and subsidized rideshare programs as possible solutions. Her medical background helped us ensure our recommendations were helpful to patients in real situations.
    The changes should be implemented with the help of the Ventura County Health Care Agency (VCHCA) because of its ability to operate and its authority in public health matters. As a community partner, VCHCA can manage medical care, update policies, and coordinate the use of mobile clinics and rideshare services for older people. Partnering with the Piru Community Center can make it easier for everyone to trust and use the programs. Partnering with communities and having clear roles helps find solutions that benefit the environment and public health (Geese & Schmitt, 2023). Nonetheless, to sustain mobile healthcare, it is necessary to have funds for the units and maintenance workers, pay staff, and cooperate with local transportation companies. Investing in health education materials that are culturally sensitive will help everyone be included.
    As someone who supports this change, I plan to give more attention to the elderly in Piru and tackle the issues that block them from receiving proper healthcare. My strategy involves creating briefs with data, presenting findings to local councils, and arranging public events to increase awareness of elderly care. With the help of strong statistics and testimonials from our assessment, I will ask for priority in policy for equal transportation and healthcare resources. The agency can support this cause by sharing its support for the recommendations, helping with grant applications, and including these ideas in future county health plans. According to Durrance-Bagale et al. (2022), working with public agencies helps make community-engaged advocacy more successful and sustainable. In addition, participatory governance models are often important for effective advocacy since they bring together health stakeholders and residents to create solutions that include everyone.
    Collaboration with reliable organizations and active community involvement will help close the healthcare divide for the elderly in Piru. Advocacy should be based on facts and include the people who are most affected. Supporting local people and working with health care agencies and policymakers promotes lasting change. We must keep collaborating, getting policy support, and engaging the community as we focus on mobile clinics and transportation. It has shown that working with clinical knowledge, local efforts, and partnerships is key to success. Using this approach, we can make noticeable improvements in senior health, making Piru an example for others in rural healthcare.
    #2
    For my population health project, I worked with Brianna Madson, an RN-BSN who has a lot of insight into what’s going on in the community. She not only resides in this area but also works as an orthopedic clinical nurse coordinator at a nearby surgical hospital. We talked about how mental health is a big issue in Northwest Hills, especially for teens and adults dealing with stress, social isolation, and financial barriers. Bri mentioned that even though people say they care about their health, a lot of them avoid seeking care because of cost or not realizing how serious things can get. We both agreed that mental health support needs to be easier to access and more visible in the community.
    One community stakeholder that could really help support this change is the Northwest Austin Civic Association (NWACA). They’re already involved in local events and outreach, so they could help with promoting mental health programs to spread awareness and even providing space for community events. Some of the resources needed would include funding for education campaigns and local mental health providers.
    As part of my advocacy, I’m really focused on helping reduce stigma and making it easier for people to find support. One of our SMART goals is to start a peer mentorship program for teens at Anderson High School by the end of this year. Having NWACA on board would make it easier to connect with families and get the word out. With their help and support from places like UT Health Austin, we can make mental health care feel more normal and accessible for everyone in the community.

  • [Solved] Business Finance – Management Business Finance – Management ASSIGNMENT (APA, NO PLAGARISM, GREAT WORK, ON TIME) here

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    Business Assignment – ## The_democratization_of_global_AI.pdf – Week7.docx – DecisionAI.pdf – Usability_and_responsivenessAI.pdf – Can_Building_Artificially_IntAI.pdf – ChatGPT_for_Educational_Purposes_Investigating_the_Impact_of_Knowledge_Management_Factors_on_Student_Satisfac…

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    Business Assignment

    – ## The_democratization_of_global_AI.pdf

    – Week7.docx
    – DecisionAI.pdf
    – Usability_and_responsivenessAI.pdf
    – Can_Building_Artificially_IntAI.pdf
    – ChatGPT_for_Educational_Purposes_Investigating_the_Impact_of_Knowledge_Management_Factors_on_Student_Satisfaction_and_Continuous_UsageAI.pdf

    **## The_democratization_of_global_AI.pdf**

    nature machine intelligence Volume 6 | March 2024 | 246–248 | 246

    https://doi.org/10.1038/s42256-024-00811-z

    Comment

    The democratization of global AI governance
    and the role of tech companies

    Eva Erman & Markus Furendal

    Can non-state multinational tech companies
    counteract the potential democratic deficit
    in the emerging global governance of AI? We
    argue that although they may strengthen core
    values of democracy such as accountability
    and transparency, they currently lack the right
    kind of authority to democratize global AI
    governance.

    After a period of intense fascination with artificial intelligence (AI)
    applications, including large language models (LLMs) such as ChatGPT,
    the public discussion is quickly turning toward the issue of the social,
    political and ethical effects of these technologies. Several regulation
    and governance initiatives are under way at national and regional levels.
    However, because cutting-edge AI development often takes place in
    multinational companies or international research labs, and AI tech-
    nology creates cross-border externalities, an additional level of trans-
    boundary regulation and cooperation is needed to solve problems or
    provide goods associated with AI technologies. The ‘global governance
    of AI’ can be said to refer to the rules, processes and decision procedures
    established by governments, international and intergovernmental
    organizations, non-state and private actors to regulate the develop-
    ment and deployment of those systems1,2. It includes soft regulations
    such as internal ethics guidelines in multinational AI-developing
    companies like Microsoft, and the ‘Bletchley declaration’ signed by
    28 countries and the European Union (EU) in 2023. It can also take the
    form of hard regulations, such as the AI Act currently under negotiation
    in the EU. Unlike the national level, regulatory efforts at the global level
    typically lack a clearly defined central institution or hierarchy. This
    means that global AI governance initiatives are partly overlapping and
    not always aligned, and are best described by the concept of ‘regime
    complex’ from international relations theory3.

    Despite the rapid pace at which this regime complex is develop-
    ing, little attention has been paid to how democratic the processes
    by which it takes shape are. It has become a trope for AI-developing
    companies to speak of a need to ‘democratize’ AI, but this often means
    simply that AI technology should be made more accessible4. Moreover,
    when the democratization of AI governance is discussed, a common
    approach is to evaluate proposals by whether they can successfully
    prevent ‘bad’ outcomes such as AI bias or existential risks, or make
    ‘good’ outcomes such as increased economic productivity more likely5.
    Similarly, the public discussion about AI regulation tends to focus on
    the pros, cons and viability of concrete proposals, such as whether AI
    development should be put on hold, to enable research into the effects
    of AI to catch up6, or whether we should create a new global institution
    akin to the International Atomic Energy Agency7. The problem with

    such an outcome-focused understanding, however, is that it reduces
    AI governance to a challenge of executing an agenda that is already set,
    thereby overlooking who has influence over the agenda and in what
    ways. It thus directs our attention towards the effects of governance
    mechanisms rather than the societal goals pursued and the means by
    which to achieve them. However, this fails to take the normative ideal
    of democracy seriously. In broad strokes, political theorists have sug-
    gested that governance arrangements are democratic to the extent
    that those affected by the decisions have a direct or indirect say in the
    decision-making on equal terms8. For AI governance to be democratic,
    this entails that those who are affected by AI technology should identify
    and decide upon the goals of AI governance collectively.

    This ideal seems unattainable at the global level. Global institu-
    tions are typically said to suffer from a democratic deficit, as it is dif-
    ficult for citizens to stay informed and exercise influence over political
    processes far removed from their daily lives. In response to this chal-
    lenge, earlier debates have often gravitated toward the democratic
    potential of non-state actors such as non-governmental organizations
    (NGOs), advocacy groups and social movements. The hope is that such
    civil society actors could represent the interests of citizens and make
    sure they appear in the decision processes of international organiza-
    tions and institutions, and that they could function as watchdogs, hold-
    ing those who wield power accountable. It is suggested that, ideally,
    civil society actors can thereby help democratize global governance,
    by promoting more inclusion, representation and transparency9,10.
    This makes it appropriate to ask whether non-state actors may help
    to democratize the global governance of AI.

    We suggest that one should not be too optimistic. This is primarily
    because in global AI governance, one kind of non-state actors is far more
    prominent than the civil society actors usually entrusted to help offset
    democratic deficits: AI-developing tech companies. The machine learn-
    ing approach to AI is, by now, so resource-intensive that breakthroughs
    are restricted to multinational corporations, such as Microsoft and its
    affiliate OpenAI, or start-ups funded by wealthy individuals, such as
    Anthropic. At the same time, a narrative is being cultivated about AI
    technology as inherently complex and difficult to understand, and of
    politics as so cumbersome that ill-informed elected officials are likely
    to cause more harm than good if they try to regulate AI on their own.
    The CEO of OpenAI, for instance, has not only provided policy advice
    at a US Senate subcommittee hearing, but also privately met with US
    lawmakers as well as the leaders of several European countries11.

    Listening to technological experts might be necessary in the process
    of finding suitable regulation for a rapidly moving policy area. At best,
    involving non-state actors could help to produce outcomes that are
    preferable, albeit not more democratic, than the alternative. At worst,
    it enables regulatory capture by companies that can hardly be said
    to represent the voices of ordinary people, let alone of marginalized
    groups12. It is thus crucial to ask what role tech companies may have
    in the democratization of global AI governance, one of our age’s most

    Check for updates

    [http://www.nature.com/natmachintell](http://www.nature.com/natmachintell)

    [https://doi.org/10.1038/s42256-024-00811-z](https://doi.org/10.1038/s42256-024-00811-z)

    [http://crossmark.crossref.org/dialog/?doi=10.1038/s42256-024-00811-z&domain=pdf](http://crossmark.crossref.org/dialog/?doi=10.1038/s42256-024-00811-z&domain=pdf)

    nature machine intelligence Volume 6 | March 2024 | 246–248 | 247

    Comment

    between (democratic) states in international organizations, non-state
    actors with moral (and possibly those with epistemic) authority may
    become democratic agents in a similar way in the future.

    Although the prospects for tech companies with market author-
    ity becoming democratic agents remain bleak, we argue that they may
    still become ‘agents of democracy’— that is, agents that strengthen the
    core values of democracy in their decision-making, such as the values
    of accountability, transparency, inclusion and deliberation. Non-state
    actors with moral authority, such as AlgorithmWatch, may be said to
    already be agents of democracy by providing input on ethical and human
    rights related considerations, and efforts to ensure that algorithmic
    decision-making is used in ways that are consistent with democratic
    values and principles. By contrast, market authorities operate within
    the structure and logic of the market, and may thus appear less likely to
    improve their democratic credentials in ways that scholars have hoped
    for. However, one should not disregard the fact that multinational com-
    panies often publicly support democratic values such as transparency,
    accountability and respect for human rights, in their own AI development
    and in their interactions with lawmakers. The most charitable interpreta-
    tion of the role of tech companies in the global governance of AI hence
    says that they could, in principle, act as agents of democracy1,5, as long
    as their commitments to democratic values are not simply an attempt
    to gain support and trust from consumers through ‘ethics washing’15.
    Importantly, however, although they may strengthen the empirical pre-
    requisites for future democratization of global AI governance by acting
    as agents of democracy, this does not take them closer to becoming
    democratic agents themselves and as such contribute to democratization.

    Conclusion
    AI is often perceived to be both a great threat and a promise to democ-
    racy. Pessimists worry about the way LLMs and other forms of AI can
    undermine communication and trust. Optimists point to how AI ena-
    bles technological innovations in voting procedures, or enables more
    voices to be heard in the democratic process, although rarely exploring
    this in light of existing democratic theories. In this Comment, we have
    suggested that the public debate should also recognise the distinct and
    additional point that the governance of AI should be as democratic as
    possible. Given the effect that AI technology already has on societies,
    it is crucial that there are democratically legitimate channels for the
    people affected by AI to have a say about how it is being developed and
    deployed. Specifically, we have argued that, although some non-state
    actors — most probably those with moral or epistemic authority — may
    become democratic agents in the future, and as such contribute to the
    democratization of global AI governance, most of them — in particular
    those with market authority — are more likely to increase their demo-
    cratic credentials as agents of democracy, improving the empirical
    prerequisites for future democratization.

    Eva Erman   1,2 & Markus Furendal   1,2

    1Department of Political Science, Stockholm University,
    Stockholm, Sweden. 2These authors contributed equally:
    Eva Erman, Markus Furendal.

    e-mail: eva.erman@statsvet.su.se

    Published online: 8 March 2024

    References
    1. Erman, E. & Furendal, M. Moral Philos. Politics 9, 2 (2022).
    2. Zürn, M. In The Oxford Handbook of Governance (ed. Levi-Faur, D.)

    (Oxford Univ. Press, 2012).

    important policy areas. In this Comment, we make two claims. First,
    the democratic potential of non-state actors depends on whether they
    wield epistemic, market or moral authority in global AI politics. Sec-
    ond, although including non-state actors could improve the prospects
    for future democratization of AI, the prospects for them becoming
    democratic agents of the kind that contribute to the democratization
    of global AI governance appear bleak. These insights should inform
    the discussion around the democratic challenges facing the global
    governance of AI.

    Forms of authority and the democratic role of tech
    companies
    AI-developing companies have come to exercise considerable influ-
    ence over the emerging global governance of AI in two overlapping
    ways13. First, they possess epistemic authority, rooted in their position
    as trustworthy judges of what constitutes knowledge and acceptable
    evidence in the AI domain. In this role, they not only develop AI but
    also inform the production and dissemination of knowledge, which
    in turn could shape public opinion and policy decisions. OpenAI and
    DeepMind, for example, partly function as research institutes, probing
    the limits of the capabilities of AI technologies in research papers that
    inform regulatory efforts. Second, they wield market authority and
    exert influence over economic and political decisions. For example,
    Microsoft arguably has notable power over AI development and regu-
    lation since its recent acquisition of the coding platform GitHub and
    investments in the AI-developing company OpenAI, which in turn has
    lobbied lawmakers in the negotiations on the EU AI Act14. Given that the
    category of non-state actors includes companies such as these, simply
    granting access to non-state actors is not guaranteed to democratize
    the global governance of AI.

    It is clear that tech companies cannot be considered to be ‘demo-
    cratic agents’, by which we mean agents that decide on policies and laws
    ‘on behalf’ of others, as no one has in fact authorised them to do so. In
    global governance, this occurs either by direct authorization through
    a democratic procedure (such as when EU citizens elect the EU parlia-
    ment) or by indirect authorization through delegation by a directly
    authorised body (such as when member state governments appoint
    members in the EU’s European Commission). When tech companies
    are invited into regulatory processes, however, they do not repre-
    sent anyone but themselves. And even if they attempted to transmit
    citizens’ concerns into the decision process of international organiza-
    tions, that would not be enough to make them democratic agents, as
    their authority has not arisen from the rightful source. This political–
    theoretical analysis suggests that, although tech companies can be said
    to contribute to improved global governance in many ways, by fulfilling
    different kinds of rightful ends, they cannot reduce the democratic
    deficit in global AI governance.

    That said, indirect authorization has taken place in more estab-
    lished policy areas in global governance, in which non-state actors have
    become democratic agents through delegation of authority, having
    crucial roles in several phases of the policy cycle of international organi-
    zations. The International Committee of the Red Cross, for example, has
    mandate under the Geneva Convention to monitor the implementation
    of international humanitarian law. What is important to notice in these
    cases, however, is that authority is typically delegated not to companies
    but instead to NGOs and other civil society actors, who exert a kind of
    moral authority derived from the fact that their mission is to promote
    what are generally seen as morally desirable goals. Arguably, with more
    international legislation in the AI domain, and deepened collaboration

    [http://www.nature.com/natmachintell](http://www.nature.com/natmachintell)

    [http://orcid.org/0000-0001-7096-9157](http://orcid.org/0000-0001-7096-9157)

    [http://orcid.org/0000-0002-2378-750X](http://orcid.org/0000-0002-2378-750X)

    [mailto:eva.erman@statsvet.su.se](mailto:eva.erman@statsvet.su.se)

    nature machine intelligence Volume 6 | March 2024 | 246–248 | 248

    Comment

    3. Tallberg, J., Erman, E., Furendal, M., Geith, J., Klamberg, M. & Lundgren, M. Int. Stud. Rev.
    25, 3 (2023).

    4. Seger, E., Ovadya, A., Siddarth, D., Garfinkel, B., Dafoe, A. In Proc. 2023 AAAI/ACM
    Conference on AI, Ethics, and Society https://doi.org/10.1145/3600211.3604693 (2023).

    5. Erman, E. & Furendal, M. Polit. Stud. https://doi.org/10.1177/00323217221126665 (2022).
    6. Future of Life Institute. https://go.nature.com/44Apd9V (accessed 13 June 2023).
    7. Altman, S., Brockman, G. & Sutskever, I. https://go.nature.com/3I867xV (accessed 22 May

    2023).
    8. Valentini, L. Perspect. Politics 12, 4 (2014).
    9. Nanz, P., Kilssing, C. & Steffek, J. (eds.). Civil Society Participation in European and Global

    Governance (Palgrave Macmillan, 2008).
    10. Dryzek, J. & Tanasoca, A. Democratizing Global Justice: Deliberating Global Goals

    (Cambridge Univ. Press, 2021).

    11. Kang, C. The New York Times https://go.nature.com/3uLG3W5 (7 June 2023).
    12. Free Press. https://go.nature.com/42XjCtJ (8 May 2023).
    13. Hall, R.B. Harv. Int. Rev. 27, 2 (2005).
    14. Perrigo, B. Time https://go.nature.com/3Tax0qY (20 June 2023).
    15. Bietti, E. In FAT* ’20: Proc. 2020 Conference on Fairness, Accountability, and Transparency

    210–219 https://doi.org/10.1145/3351095.3372860 (2020).

    Competing interests
    The authors declare no competing interests.

    Additional information
    Peer review information : Nature Machine Intelligence thanks the anonymous reviewer(s) for
    their contribution to the peer review of this work.

    [http://www.nature.com/natmachintell](http://www.nature.com/natmachintell)

    [https://doi.org/10.1145/3600211.3604693](https://doi.org/10.1145/3600211.3604693)

    [https://doi.org/10.1177/00323217221126665](https://doi.org/10.1177/00323217221126665)

    [https://go.nature.com/44Apd9V](https://go.nature.com/44Apd9V)

    [https://go.nature.com/3I867xV](https://go.nature.com/3I867xV)

    [https://go.nature.com/3uLG3W5](https://go.nature.com/3uLG3W5)

    [https://go.nature.com/42XjCtJ](https://go.nature.com/42XjCtJ)

    [https://go.nature.com/3Tax0qY](https://go.nature.com/3Tax0qY)

    [https://doi.org/10.1145/3351095.3372860](https://doi.org/10.1145/3351095.3372860)

    Reproduced with permission of copyright owner. Further reproduction
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    – The democratization of global AI governance and the role of tech companies

    – Forms of authority and the democratic role of tech companies

    – Conclusion

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    **## The_democratization_of_global_AI.pdf**

    nature machine intelligence Volume 6 | March 2024 | 246–248 | 246

    https://doi.org/10.1038/s42256-024-00811-z

    Comment

    The democratization of global AI governance
    and the role of tech companies

    Eva Erman & Markus Furendal

    Can non-state multinational tech companies
    counteract the potential democratic deficit
    in the emerging global governance of AI? We
    argue that although they may strengthen core
    values of democracy such as accountability
    and transparency, they currently lack the right
    kind of authority to democratize global AI
    governance.

    After a period of intense fascination with artificial intelligence (AI)
    applications, including large language models (LLMs) such as ChatGPT,
    the public discussion is quickly turning toward the issue of the social,
    political and ethical effects of these technologies. Several regulation
    and governance initiatives are under way at national and regional levels.
    However, because cutting-edge AI development often takes place in
    multinational companies or international research labs, and AI tech-
    nology creates cross-border externalities, an additional level of trans-
    boundary regulation and cooperation is needed to solve problems or
    provide goods associated with AI technologies. The ‘global governance
    of AI’ can be said to refer to the rules, processes and decision procedures
    established by governments, international and intergovernmental
    organizations, non-state and private actors to regulate the develop-
    ment and deployment of those systems1,2. It includes soft regulations
    such as internal ethics guidelines in multinational AI-developing
    companies like Microsoft, and the ‘Bletchley declaration’ signed by
    28 countries and the European Union (EU) in 2023. It can also take the
    form of hard regulations, such as the AI Act currently under negotiation
    in the EU. Unlike the national level, regulatory efforts at the global level
    typically lack a clearly defined central institution or hierarchy. This
    means that global AI governance initiatives are partly overlapping and
    not always aligned, and are best described by the concept of ‘regime
    complex’ from international relations theory3.

    Despite the rapid pace at which this regime complex is develop-
    ing, little attention has been paid to how democratic the processes
    by which it takes shape are. It has become a trope for AI-developing
    companies to speak of a need to ‘democratize’ AI, but this often means
    simply that AI technology should be made more accessible4. Moreover,
    when the democratization of AI governance is discussed, a common
    approach is to evaluate proposals by whether they can successfully
    prevent ‘bad’ outcomes such as AI bias or existential risks, or make
    ‘good’ outcomes such as increased economic productivity more likely5.
    Similarly, the public discussion about AI regulation tends to focus on
    the pros, cons and viability of concrete proposals, such as whether AI
    development should be put on hold, to enable research into the effects
    of AI to catch up6, or whether we should create a new global institution
    akin to the International Atomic Energy Agency7. The problem with

    such an outcome-focused understanding, however, is that it reduces
    AI governance to a challenge of executing an agenda that is already set,
    thereby overlooking who has influence over the agenda and in what
    ways. It thus directs our attention towards the effects of governance
    mechanisms rather than the societal goals pursued and the means by
    which to achieve them. However, this fails to take the normative ideal
    of democracy seriously. In broad strokes, political theorists have sug-
    gested that governance arrangements are democratic to the extent
    that those affected by the decisions have a direct or indirect say in the
    decision-making on equal terms8. For AI governance to be democratic,
    this entails that those who are affected by AI technology should identify
    and decide upon the goals of AI governance collectively.

    This ideal seems unattainable at the global level. Global institu-
    tions are typically said to suffer from a democratic deficit, as it is dif-
    ficult for citizens to stay informed and exercise influence over political
    processes far removed from their daily lives. In response to this chal-
    lenge, earlier debates have often gravitated toward the democratic
    potential of non-state actors such as non-governmental organizations
    (NGOs), advocacy groups and social movements. The hope is that such
    civil society actors could represent the interests of citizens and make
    sure they appear in the decision processes of international organiza-
    tions and institutions, and that they could function as watchdogs, hold-
    ing those who wield power accountable. It is suggested that, ideally,
    civil society actors can thereby help democratize global governance,
    by promoting more inclusion, representation and transparency9,10.
    This makes it appropriate to ask whether non-state actors may help
    to democratize the global governance of AI.

    We suggest that one should not be too optimistic. This is primarily
    because in global AI governance, one kind of non-state actors is far more
    prominent than the civil society actors usually entrusted to help offset
    democratic deficits: AI-developing tech companies. The machine learn-
    ing approach to AI is, by now, so resource-intensive that breakthroughs
    are restricted to multinational corporations, such as Microsoft and its
    affiliate OpenAI, or start-ups funded by wealthy individuals, such as
    Anthropic. At the same time, a narrative is being cultivated about AI
    technology as inherently complex and difficult to understand, and of
    politics as so cumbersome that ill-informed elected officials are likely
    to cause more harm than good if they try to regulate AI on their own.
    The CEO of OpenAI, for instance, has not only provided policy advice
    at a US Senate subcommittee hearing, but also privately met with US
    lawmakers as well as the leaders of several European countries11.

    Listening to technological experts might be necessary in the process
    of finding suitable regulation for a rapidly moving policy area. At best,
    involving non-state actors could help to produce outcomes that are
    preferable, albeit not more democratic, than the alternative. At worst,
    it enables regulatory capture by companies that can hardly be said
    to represent the voices of ordinary people, let alone of marginalized
    groups12. It is thus crucial to ask what role tech companies may have
    in the democratization of global AI governance, one of our age’s most

    Check for updates

    [http://www.nature.com/natmachintell](http://www.nature.com/natmachintell)

    [https://doi.org/10.1038/s42256-024-00811-z](https://doi.org/10.1038/s42256-024-00811-z)

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    nature machine intelligence Volume 6 | March 2024 | 246–248 | 247

    Comment

    between (democratic) states in international organizations, non-state
    actors with moral (and possibly those with epistemic) authority may
    become democratic agents in a similar way in the future.

    Although the prospects for tech companies with market author-
    ity becoming democratic agents remain bleak, we argue that they may
    still become ‘agents of democracy’— that is, agents that strengthen the
    core values of democracy in their decision-making, such as the values
    of accountability, transparency, inclusion and deliberation. Non-state
    actors with moral authority, such as AlgorithmWatch, may be said to
    already be agents of democracy by providing input on ethical and human
    rights related considerations, and efforts to ensure that algorithmic
    decision-making is used in ways that are consistent with democratic
    values and principles. By contrast, market authorities operate within
    the structure and logic of the market, and may thus appear less likely to
    improve their democratic credentials in ways that scholars have hoped
    for. However, one should not disregard the fact that multinational com-
    panies often publicly support democratic values such as transparency,
    accountability and respect for human rights, in their own AI development
    and in their interactions with lawmakers. The most charitable interpreta-
    tion of the role of tech companies in the global governance of AI hence
    says that they could, in principle, act as agents of democracy1,5, as long
    as their commitments to democratic values are not simply an attempt
    to gain support and trust from consumers through ‘ethics washing’15.
    Importantly, however, although they may strengthen the empirical pre-
    requisites for future democratization of global AI governance by acting
    as agents of democracy, this does not take them closer to becoming
    democratic agents themselves and as such contribute to democratization.

    Conclusion
    AI is often perceived to be both a great threat and a promise to democ-
    racy. Pessimists worry about the way LLMs and other forms of AI can
    undermine communication and trust. Optimists point to how AI ena-
    bles technological innovations in voting procedures, or enables more
    voices to be heard in the democratic process, although rarely exploring
    this in light of existing democratic theories. In this Comment, we have
    suggested that the public debate should also recognise the distinct and
    additional point that the governance of AI should be as democratic as
    possible. Given the effect that AI technology already has on societies,
    it is crucial that there are democratically legitimate channels for the
    people affected by AI to have a say about how it is being developed and
    deployed. Specifically, we have argued that, although some non-state
    actors — most probably those with moral or epistemic authority — may
    become democratic agents in the future, and as such contribute to the
    democratization of global AI governance, most of them — in particular
    those with market authority — are more likely to increase their demo-
    cratic credentials as agents of democracy, improving the empirical
    prerequisites for future democratization.

    Eva Erman   1,2 & Markus Furendal   1,2

    1Department of Political Science, Stockholm University,
    Stockholm, Sweden. 2These authors contributed equally:
    Eva Erman, Markus Furendal.

    e-mail: eva.erman@statsvet.su.se

    Published online: 8 March 2024

    References
    1. Erman, E. & Furendal, M. Moral Philos. Politics 9, 2 (2022).
    2. Zürn, M. In The Oxford Handbook of Governance (ed. Levi-Faur, D.)

    (Oxford Univ. Press, 2012).

    important policy areas. In this Comment, we make two claims. First,
    the democratic potential of non-state actors depends on whether they
    wield epistemic, market or moral authority in global AI politics. Sec-
    ond, although including non-state actors could improve the prospects
    for future democratization of AI, the prospects for them becoming
    democratic agents of the kind that contribute to the democratization
    of global AI governance appear bleak. These insights should inform
    the discussion around the democratic challenges facing the global
    governance of AI.

    Forms of authority and the democratic role of tech
    companies
    AI-developing companies have come to exercise considerable influ-
    ence over the emerging global governance of AI in two overlapping
    ways13. First, they possess epistemic authority, rooted in their position
    as trustworthy judges of what constitutes knowledge and acceptable
    evidence in the AI domain. In this role, they not only develop AI but
    also inform the production and dissemination of knowledge, which
    in turn could shape public opinion and policy decisions. OpenAI and
    DeepMind, for example, partly function as research institutes, probing
    the limits of the capabilities of AI technologies in research papers that
    inform regulatory efforts. Second, they wield market authority and
    exert influence over economic and political decisions. For example,
    Microsoft arguably has notable power over AI development and regu-
    lation since its recent acquisition of the coding platform GitHub and
    investments in the AI-developing company OpenAI, which in turn has
    lobbied lawmakers in the negotiations on the EU AI Act14. Given that the
    category of non-state actors includes companies such as these, simply
    granting access to non-state actors is not guaranteed to democratize
    the global governance of AI.

    It is clear that tech companies cannot be considered to be ‘demo-
    cratic agents’, by which we mean agents that decide on policies and laws
    ‘on behalf’ of others, as no one has in fact authorised them to do so. In
    global governance, this occurs either by direct authorization through
    a democratic procedure (such as when EU citizens elect the EU parlia-
    ment) or by indirect authorization through delegation by a directly
    authorised body (such as when member state governments appoint
    members in the EU’s European Commission). When tech companies
    are invited into regulatory processes, however, they do not repre-
    sent anyone but themselves. And even if they attempted to transmit
    citizens’ concerns into the decision process of international organiza-
    tions, that would not be enough to make them democratic agents, as
    their authority has not arisen from the rightful source. This political–
    theoretical analysis suggests that, although tech companies can be said
    to contribute to improved global governance in many ways, by fulfilling
    different kinds of rightful ends, they cannot reduce the democratic
    deficit in global AI governance.

    That said, indirect authorization has taken place in more estab-
    lished policy areas in global governance, in which non-state actors have
    become democratic agents through delegation of authority, having
    crucial roles in several phases of the policy cycle of international organi-
    zations. The International Committee of the Red Cross, for example, has
    mandate under the Geneva Convention to monitor the implementation
    of international humanitarian law. What is important to notice in these
    cases, however, is that authority is typically delegated not to companies
    but instead to NGOs and other civil society actors, who exert a kind of
    moral authority derived from the fact that their mission is to promote
    what are generally seen as morally desirable goals. Arguably, with more
    international legislation in the AI domain, and deepened collaboration

    [http://www.nature.com/natmachintell](http://www.nature.com/natmachintell)

    [http://orcid.org/0000-0001-7096-9157](http://orcid.org/0000-0001-7096-9157)

    [http://orcid.org/0000-0002-2378-750X](http://orcid.org/0000-0002-2378-750X)

    [mailto:eva.erman@statsvet.su.se](mailto:eva.erman@statsvet.su.se)

    nature machine intelligence Volume 6 | March 2024 | 246–248 | 248

    Comment

    3. Tallberg, J., Erman, E., Furendal, M., Geith, J., Klamberg, M. & Lundgren, M. Int. Stud. Rev.
    25, 3 (2023).

    4. Seger, E., Ovadya, A., Siddarth, D., Garfinkel, B., Dafoe, A. In Proc. 2023 AAAI/ACM
    Conference on AI, Ethics, and Society https://doi.org/10.1145/3600211.3604693 (2023).

    5. Erman, E. & Furendal, M. Polit. Stud. https://doi.org/10.1177/00323217221126665 (2022).
    6. Future of Life Institute. https://go.nature.com/44Apd9V (accessed 13 June 2023).
    7. Altman, S., Brockman, G. & Sutskever, I. https://go.nature.com/3I867xV (accessed 22 May

    2023).
    8. Valentini, L. Perspect. Politics 12, 4 (2014).
    9. Nanz, P., Kilssing, C. & Steffek, J. (eds.). Civil Society Participation in European and Global

    Governance (Palgrave Macmillan, 2008).
    10. Dryzek, J. & Tanasoca, A. Democratizing Global Justice: Deliberating Global Goals

    (Cambridge Univ. Press, 2021).

    11. Kang, C. The New York Times https://go.nature.com/3uLG3W5 (7 June 2023).
    12. Free Press. https://go.nature.com/42XjCtJ (8 May 2023).
    13. Hall, R.B. Harv. Int. Rev. 27, 2 (2005).
    14. Perrigo, B. Time https://go.nature.com/3Tax0qY (20 June 2023).
    15. Bietti, E. In FAT* ’20: Proc. 2020 Conference on Fairness, Accountability, and Transparency

    210–219 https://doi.org/10.1145/3351095.3372860 (2020).

    Competing interests
    The authors declare no competing interests.

    Additional information
    Peer review information : Nature Machine Intelligence thanks the anonymous reviewer(s) for
    their contribution to the peer review of this work.

    [http://www.nature.com/natmachintell](http://www.nature.com/natmachintell)

    [https://doi.org/10.1145/3600211.3604693](https://doi.org/10.1145/3600211.3604693)

    [https://doi.org/10.1177/00323217221126665](https://doi.org/10.1177/00323217221126665)

    [https://go.nature.com/44Apd9V](https://go.nature.com/44Apd9V)

    [https://go.nature.com/3I867xV](https://go.nature.com/3I867xV)

    [https://go.nature.com/3uLG3W5](https://go.nature.com/3uLG3W5)

    [https://go.nature.com/42XjCtJ](https://go.nature.com/42XjCtJ)

    [https://go.nature.com/3Tax0qY](https://go.nature.com/3Tax0qY)

    [https://doi.org/10.1145/3351095.3372860](https://doi.org/10.1145/3351095.3372860)

    Reproduced with permission of copyright owner. Further reproduction
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    – The democratization of global AI governance and the role of tech companies

    – Forms of authority and the democratic role of tech companies

    – Conclusion

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    **## The_democratization_of_global_AI.pdf**

    nature machine intelligence Volume 6 | March 2024 | 246–248 | 246

    https://doi.org/10.1038/s42256-024-00811-z

    Comment

    The democratization of global AI governance
    and the role of tech companies

    Eva Erman & Markus Furendal

    Can non-state multinational tech companies
    counteract the potential democratic deficit
    in the emerging global governance of AI? We
    argue that although they may strengthen core
    values of democracy such as accountability
    and transparency, they currently lack the right
    kind of authority to democratize global AI
    governance.

    After a period of intense fascination with artificial intelligence (AI)
    applications, including large language models (LLMs) such as ChatGPT,
    the public discussion is quickly turning toward the issue of the social,
    political and ethical effects of these technologies. Several regulation
    and governance initiatives are under way at national and regional levels.
    However, because cutting-edge AI development often takes place in
    multinational companies or international research labs, and AI tech-
    nology creates cross-border externalities, an additional level of trans-
    boundary regulation and cooperation is needed to solve problems or
    provide goods associated with AI technologies. The ‘global governance
    of AI’ can be said to refer to the rules, processes and decision procedures
    established by governments, international and intergovernmental
    organizations, non-state and private actors to regulate the develop-
    ment and deployment of those systems1,2. It includes soft regulations
    such as internal ethics guidelines in multinational AI-developing
    companies like Microsoft, and the ‘Bletchley declaration’ signed by
    28 countries and the European Union (EU) in 2023. It can also take the
    form of hard regulations, such as the AI Act currently under negotiation
    in the EU. Unlike the national level, regulatory efforts at the global level
    typically lack a clearly defined central institution or hierarchy. This
    means that global AI governance initiatives are partly overlapping and
    not always aligned, and are best described by the concept of ‘regime
    complex’ from international relations theory3.

    Despite the rapid pace at which this regime complex is develop-
    ing, little attention has been paid to how democratic the processes
    by which it takes shape are. It has become a trope for AI-developing
    companies to speak of a need to ‘democratize’ AI, but this often means
    simply that AI technology should be made more accessible4. Moreover,
    when the democratization of AI governance is discussed, a common
    approach is to evaluate proposals by whether they can successfully
    prevent ‘bad’ outcomes such as AI bias or existential risks, or make
    ‘good’ outcomes such as increased economic productivity more likely5.
    Similarly, the public discussion about AI regulation tends to focus on
    the pros, cons and viability of concrete proposals, such as whether AI
    development should be put on hold, to enable research into the effects
    of AI to catch up6, or whether we should create a new global institution
    akin to the International Atomic Energy Agency7. The problem with

    such an outcome-focused understanding, however, is that it reduces
    AI governance to a challenge of executing an agenda that is already set,
    thereby overlooking who has influence over the agenda and in what
    ways. It thus directs our attention towards the effects of governance
    mechanisms rather than the societal goals pursued and the means by
    which to achieve them. However, this fails to take the normative ideal
    of democracy seriously. In broad strokes, political theorists have sug-
    gested that governance arrangements are democratic to the extent
    that those affected by the decisions have a direct or indirect say in the
    decision-making on equal terms8. For AI governance to be democratic,
    this entails that those who are affected by AI technology should identify
    and decide upon the goals of AI governance collectively.

    This ideal seems unattainable at the global level. Global institu-
    tions are typically said to suffer from a democratic deficit, as it is dif-
    ficult for citizens to stay informed and exercise influence over political
    processes far removed from their daily lives. In response to this chal-
    lenge, earlier debates have often gravitated toward the democratic
    potential of non-state actors such as non-governmental organizations
    (NGOs), advocacy groups and social movements. The hope is that such
    civil society actors could represent the interests of citizens and make
    sure they appear in the decision processes of international organiza-
    tions and institutions, and that they could function as watchdogs, hold-
    ing those who wield power accountable. It is suggested that, ideally,
    civil society actors can thereby help democratize global governance,
    by promoting more inclusion, representation and transparency9,10.
    This makes it appropriate to ask whether non-state actors may help
    to democratize the global governance of AI.

    We suggest that one should not be too optimistic. This is primarily
    because in global AI governance, one kind of non-state actors is far more
    prominent than the civil society actors usually entrusted to help offset
    democratic deficits: AI-developing tech companies. The machine learn-
    ing approach to AI is, by now, so resource-intensive that breakthroughs
    are restricted to multinational corporations, such as Microsoft and its
    affiliate OpenAI, or start-ups funded by wealthy individuals, such as
    Anthropic. At the same time, a narrative is being cultivated about AI
    technology as inherently complex and difficult to understand, and of
    politics as so cumbersome that ill-informed elected officials are likely
    to cause more harm than good if they try to regulate AI on their own.
    The CEO of OpenAI, for instance, has not only provided policy advice
    at a US Senate subcommittee hearing, but also privately met with US
    lawmakers as well as the leaders of several European countries11.

    Listening to technological experts might be necessary in the process
    of finding suitable regulation for a rapidly moving policy area. At best,
    involving non-state actors could help to produce outcomes that are
    preferable, albeit not more democratic, than the alternative. At worst,
    it enables regulatory capture by companies that can hardly be said
    to represent the voices of ordinary people, let alone of marginalized
    groups12. It is thus crucial to ask what role tech companies may have
    in the democratization of global AI governance, one of our age’s most

    Check for updates

    [http://www.nature.com/natmachintell](http://www.nature.com/natmachintell)

    [https://doi.org/10.1038/s42256-024-00811-z](https://doi.org/10.1038/s42256-024-00811-z)

    [http://crossmark.crossref.org/dialog/?doi=10.1038/s42256-024-00811-z&domain=pdf](http://crossmark.crossref.org/dialog/?doi=10.1038/s42256-024-00811-z&domain=pdf)

    nature machine intelligence Volume 6 | March 2024 | 246–248 | 247

    Comment

    between (democratic) states in international organizations, non-state
    actors with moral (and possibly those with epistemic) authority may
    become democratic agents in a similar way in the future.

    Although the prospects for tech companies with market author-
    ity becoming democratic agents remain bleak, we argue that they may
    still become ‘agents of democracy’— that is, agents that strengthen the
    core values of democracy in their decision-making, such as the values
    of accountability, transparency, inclusion and deliberation. Non-state
    actors with moral authority, such as AlgorithmWatch, may be said to
    already be agents of democracy by providing input on ethical and human
    rights related considerations, and efforts to ensure that algorithmic
    decision-making is used in ways that are consistent with democratic
    values and principles. By contrast, market authorities operate within
    the structure and logic of the market, and may thus appear less likely to
    improve their democratic credentials in ways that scholars have hoped
    for. However, one should not disregard the fact that multinational com-
    panies often publicly support democratic values such as transparency,
    accountability and respect for human rights, in their own AI development
    and in their interactions with lawmakers. The most charitable interpreta-
    tion of the role of tech companies in the global governance of AI hence
    says that they could, in principle, act as agents of democracy1,5, as long
    as their commitments to democratic values are not simply an attempt
    to gain support and trust from consumers through ‘ethics washing’15.
    Importantly, however, although they may strengthen the empirical pre-
    requisites for future democratization of global AI governance by acting
    as agents of democracy, this does not take them closer to becoming
    democratic agents themselves and as such contribute to democratization.

    Conclusion
    AI is often perceived to be both a great threat and a promise to democ-
    racy. Pessimists worry about the way LLMs and other forms of AI can
    undermine communication and trust. Optimists point to how AI ena-
    bles technological innovations in voting procedures, or enables more
    voices to be heard in the democratic process, although rarely exploring
    this in light of existing democratic theories. In this Comment, we have
    suggested that the public debate should also recognise the distinct and
    additional point that the governance of AI should be as democratic as
    possible. Given the effect that AI technology already has on societies,
    it is crucial that there are democratically legitimate channels for the
    people affected by AI to have a say about how it is being developed and
    deployed. Specifically, we have argued that, although some non-state
    actors — most probably those with moral or epistemic authority — may
    become democratic agents in the future, and as such contribute to the
    democratization of global AI governance, most of them — in particular
    those with market authority — are more likely to increase their demo-
    cratic credentials as agents of democracy, improving the empirical
    prerequisites for future democratization.

    Eva Erman   1,2 & Markus Furendal   1,2

    1Department of Political Science, Stockholm University,
    Stockholm, Sweden. 2These authors contributed equally:
    Eva Erman, Markus Furendal.

    e-mail: eva.erman@statsvet.su.se

    Published online: 8 March 2024

    References
    1. Erman, E. & Furendal, M. Moral Philos. Politics 9, 2 (2022).
    2. Zürn, M. In The Oxford Handbook of Governance (ed. Levi-Faur, D.)

    (Oxford Univ. Press, 2012).

    important policy areas. In this Comment, we make two claims. First,
    the democratic potential of non-state actors depends on whether they
    wield epistemic, market or moral authority in global AI politics. Sec-
    ond, although including non-state actors could improve the prospects
    for future democratization of AI, the prospects for them becoming
    democratic agents of the kind that contribute to the democratization
    of global AI governance appear bleak. These insights should inform
    the discussion around the democratic challenges facing the global
    governance of AI.

    Forms of authority and the democratic role of tech
    companies
    AI-developing companies have come to exercise considerable influ-
    ence over the emerging global governance of AI in two overlapping
    ways13. First, they possess epistemic authority, rooted in their position
    as trustworthy judges of what constitutes knowledge and acceptable
    evidence in the AI domain. In this role, they not only develop AI but
    also inform the production and dissemination of knowledge, which
    in turn could shape public opinion and policy decisions. OpenAI and
    DeepMind, for example, partly function as research institutes, probing
    the limits of the capabilities of AI technologies in research papers that
    inform regulatory efforts. Second, they wield market authority and
    exert influence over economic and political decisions. For example,
    Microsoft arguably has notable power over AI development and regu-
    lation since its recent acquisition of the coding platform GitHub and
    investments in the AI-developing company OpenAI, which in turn has
    lobbied lawmakers in the negotiations on the EU AI Act14. Given that the
    category of non-state actors includes companies such as these, simply
    granting access to non-state actors is not guaranteed to democratize
    the global governance of AI.

    It is clear that tech companies cannot be considered to be ‘demo-
    cratic agents’, by which we mean agents that decide on policies and laws
    ‘on behalf’ of others, as no one has in fact authorised them to do so. In
    global governance, this occurs either by direct authorization through
    a democratic procedure (such as when EU citizens elect the EU parlia-
    ment) or by indirect authorization through delegation by a directly
    authorised body (such as when member state governments appoint
    members in the EU’s European Commission). When tech companies
    are invited into regulatory processes, however, they do not repre-
    sent anyone but themselves. And even if they attempted to transmit
    citizens’ concerns into the decision process of international organiza-
    tions, that would not be enough to make them democratic agents, as
    their authority has not arisen from the rightful source. This political–
    theoretical analysis suggests that, although tech companies can be said
    to contribute to improved global governance in many ways, by fulfilling
    different kinds of rightful ends, they cannot reduce the democratic
    deficit in global AI governance.

    That said, indirect authorization has taken place in more estab-
    lished policy areas in global governance, in which non-state actors have
    become democratic agents through delegation of authority, having
    crucial roles in several phases of the policy cycle of international organi-
    zations. The International Committee of the Red Cross, for example, has
    mandate under the Geneva Convention to monitor the implementation
    of international humanitarian law. What is important to notice in these
    cases, however, is that authority is typically delegated not to companies
    but instead to NGOs and other civil society actors, who exert a kind of
    moral authority derived from the fact that their mission is to promote
    what are generally seen as morally desirable goals. Arguably, with more
    international legislation in the AI domain, and deepened collaboration

    [http://www.nature.com/natmachintell](http://www.nature.com/natmachintell)

    [http://orcid.org/0000-0001-7096-9157](http://orcid.org/0000-0001-7096-9157)

    [http://orcid.org/0000-0002-2378-750X](http://orcid.org/0000-0002-2378-750X)

    [mailto:eva.erman@statsvet.su.se](mailto:eva.erman@statsvet.su.se)

    nature machine intelligence Volume 6 | March 2024 | 246–248 | 248

    Comment

    3. Tallberg, J., Erman, E., Furendal, M., Geith, J., Klamberg, M. & Lundgren, M. Int. Stud. Rev.
    25, 3 (2023).

    4. Seger, E., Ovadya, A., Siddarth, D., Garfinkel, B., Dafoe, A. In Proc. 2023 AAAI/ACM
    Conference on AI, Ethics, and Society https://doi.org/10.1145/3600211.3604693 (2023).

    5. Erman, E. & Furendal, M. Polit. Stud. https://doi.org/10.1177/00323217221126665 (2022).
    6. Future of Life Institute. https://go.nature.com/44Apd9V (accessed 13 June 2023).
    7. Altman, S., Brockman, G. & Sutskever, I. https://go.nature.com/3I867xV (accessed 22 May

    2023).
    8. Valentini, L. Perspect. Politics 12, 4 (2014).
    9. Nanz, P., Kilssing, C. & Steffek, J. (eds.). Civil Society Participation in European and Global

    Governance (Palgrave Macmillan, 2008).
    10. Dryzek, J. & Tanasoca, A. Democratizing Global Justice: Deliberating Global Goals

    (Cambridge Univ. Press, 2021).

    11. Kang, C. The New York Times https://go.nature.com/3uLG3W5 (7 June 2023).
    12. Free Press. https://go.nature.com/42XjCtJ (8 May 2023).
    13. Hall, R.B. Harv. Int. Rev. 27, 2 (2005).
    14. Perrigo, B. Time https://go.nature.com/3Tax0qY (20 June 2023).
    15. Bietti, E. In FAT* ’20: Proc. 2020 Conference on Fairness, Accountability, and Transparency

    210–219 https://doi.org/10.1145/3351095.3372860 (2020).

    Competing interests
    The authors declare no competing interests.

    Additional information
    Peer review information : Nature Machine Intelligence thanks the anonymous reviewer(s) for
    their contribution to the peer review of this work.

    [http://www.nature.com/natmachintell](http://www.nature.com/natmachintell)

    [https://doi.org/10.1145/3600211.3604693](https://doi.org/10.1145/3600211.3604693)

    [https://doi.org/10.1177/00323217221126665](https://doi.org/10.1177/00323217221126665)

    [https://go.nature.com/44Apd9V](https://go.nature.com/44Apd9V)

    [https://go.nature.com/3I867xV](https://go.nature.com/3I867xV)

    [https://go.nature.com/3uLG3W5](https://go.nature.com/3uLG3W5)

    [https://go.nature.com/42XjCtJ](https://go.nature.com/42XjCtJ)

    [https://go.nature.com/3Tax0qY](https://go.nature.com/3Tax0qY)

    [https://doi.org/10.1145/3351095.3372860](https://doi.org/10.1145/3351095.3372860)

    Reproduced with permission of copyright owner. Further reproduction
    prohibited without permission.

    – The democratization of global AI governance and the role of tech companies

    – Forms of authority and the democratic role of tech companies

    – Conclusion

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    descriptive/observational approaches to research. – ## Week5resources.docx – ## Week5instructions.docx **## Week5resources.docx** · **“A Clear Day and No Memories”: Neurology, Philosophy, and Analogy in Kerry Tribe’s H.M.** Goulish, M. (2013). “A clear day and no memories”: Neurology, philosophy, an…

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    descriptive/observational approaches to research.

    – ## Week5resources.docx

    – ## Week5instructions.docx

    **## Week5resources.docx**

    ·
    **“A Clear Day and No Memories”: Neurology, Philosophy, and Analogy in Kerry Tribe’s H.M.**

    Goulish, M. (2013). “A clear day and no memories”: Neurology, philosophy, and analogy in Kerry Tribe’s H.M.
    _Art Journal, 72_(3), 12–29.

    ·
    [**Phineas Gage and his Frontal Lobe-The “American Crowbar Case”**](https://search.ebscohost.com/login.aspx?authtype=shib&custid=natuniv&direct=true&db=mdc&AN=23074983&site=eds-live)

    Guidotti, T. L. (2012). Phineas Gage and his frontal lobe-The “American Crowbar case”.
    _Archives of Environmental and Occupational Health, 67_(4), 249-250.

    ·
    [**The Evolution of Charles Darwin**](https://www.smithsonianmag.com/science-nature/the-evolution-of-charles-darwin-110234034/)

    Sulloway, F. (December, 2005).
    _The evolution of Charles Darwin._ Smithsonian Magazine.

    ·
    [**The Feral Child Nicknamed Genie**](https://www.psychologytoday.com/us/blog/the-superhuman-mind/201707/the-feral-child-nicknamed-genie)

    Brogaard, B. (2017, July 10). The feral child nicknamed Genie.
    _Psychology Today._

    **## Week5instructions.docx**

    **Observational/Descriptive Research**

    This week, you will learn more about the descriptive research methods scientists use to answer research questions that pertain to value or worth or how much of some variable is present. While reading about these different methods, begin to think more about how you might use each of these approaches with your specific research topic of interest.

    Generally, observational or descriptive research is the simplest and easiest research design to use. With this type of research design, you are simply observing or describing observable behaviors. The design itself is entirely ‘hands-off’, meaning you are simply making a note of what occurs naturally, without any intervention on the part of the researcher (Gravetter & Forzano, 2018). You might have video and audiotapes to review when using this approach as a way to be less obvious to participants.

    There are three basic types of descriptive research methods that psychologists frequently use, and these are
    _naturalistic observation, surveys,_ and
    _case studies_. In this week’s lesson, you will learn about each of these descriptive/observational research methods, along with the strengths and weaknesses of each approach.

    _Naturalistic observation_ is the descriptive approach Darwin used when he developed his theory of evolution while cruising in the
    _Beagle_(the name of his ship) in the Galapagos Islands (Sulloway, 2005). He formulated his theory of natural selection and the concept of
    _survival of the fittest_ through the descriptive method of naturalistic observation
    _._

    When conducting naturalistic observation, it is important to take steps to ‘blend right in’, while at the same time carefully observe whatever it is that you are studying. Your presence should go unnoticed, and as a result, you will not cause any sort of change in the behavior of the subjects you are observing. With naturalistic observation, you are trying to observe your subjects without making them aware that you are doing so. This is important to obtain a clearer picture of the truth or what is really happening. In other words, the
    _normal_ or
    _natural_ behavior of the participant. Otherwise, if they notice you are watching and paying attention, you may start to see noticeable changes in their behavior that do not reflect what they usually do. This is something called
    _subject reactivity_, and it is what you want to avoid when using naturalistic observation as the participant behavior is no longer ‘natural’ (Gravetter & Foranzo, 2018). While you might not think that others' mere presence can change or influence someone’s behavior, you will be surprised to learn that it can make a huge difference.

    The famous Hawthorne studies is perhaps one of the clearest examples of the issue of
    _subject reactivity,_ with naturalistic observation as the research method (Intellicom, 2011). With this landmark study, scientists were interested in determining whether or not the lighting that was being used in the factory would make a difference in worker productivity. So, they went in and periodically changed the lighting in the workplace. They did so by climbing up on ladders and changing the light bulbs during working hours when the workers were present. Interestingly enough, they found that these changes led to increases in productivity for all employees, regardless of the lighting itself. They eventually realized that it was the attention they were giving the workers that led to this improved performance, not the lighting. In other words, the fact that someone was paying attention to them is what caused the change in the behavior to occur. This had nothing whatsoever to do with the lighting! This is something for you to consider when using naturalistic observation as your descriptive research method. For example, in the Hawthorne studies, it is hypothesized that if the researchers had entered at night when the employees were not there, it most likely would have had no effect on their productivity. No changes in the employee behaviors would be evident. Thankfully, however, this was not the case, and a lot was learned about research subjects and participant reactivity as a result of this famous study.

    It is also important to remember with naturalistic observation, you can only study behaviors that are directly observable, meaning behaviors you can see or hear (Gravetter & Foranzo, 2018). You can not study a subject’s feelings, attitudes, values, or beliefs. This is a definite strength of the naturalistic observation design, for it is much more scientific and objective. However, at the same time, it is also a weakness in that you are limited to directly observable behaviors
    _only_. What might you do if you want to explore an individual's attitudes, beliefs, or feelings? You could opt to use a different descriptive method called a
    _survey_.

    _Surveys_ are also considered a descriptive approach to research for they allow the researcher to explore more subjective inner behaviors like a participant’s attitudes, beliefs, or values. In other words, it includes their thoughts and feelings, which are not directly observable. While this is a definite strength to the use of the survey research method, there are problems with this approach as well. More specifically, people will frequently lie or try to ‘look good’ to the researcher – even when surveys are anonymous. This is something called
    _social desirability_, and it is a genuine concern when using surveys. This issue is particularly relevant when the topic is a sensitive one (e.g., asking if they have ever engaged in illegal behavior). With surveys, researchers will typically provide participants with a statement of some sort, and they will then be asked to assess their level of agreement on a Likert-type scale of 1 to 5, or some other scale. Surveys
    are a popular research method because they are easy to use and relatively effective in assessing an individual’s inner behaviors.

    The last method of descriptive or observational research included in this week’s lesson is called a
    _case study_. A case study is a more in-depth exploration of a single subject, and it is typically only used when you have an individual who is different or unique in some way (Gravetter & Foranzo, 2018). For example, Genie the Wild Child's case is a very famous case study about a young girl who was kept isolated from the world for the first 12 years of her life (Broggard, 2017). Because of this isolation, she basically had no language development. As a result of the research on
    _Genie_, scientists came to realize that language development must occur during a critical time of overall childhood development. Otherwise, it will be delayed and difficult to obtain.

    Another famous case study includes that of Phineas Gage, the man with the railroad tine through his skull who lived but experienced significant changes in his personality due to his injury (Guidotti, 2012). Even though he lived to talk about it, he would often go into fits of rage because of the damage to his brain's amygdala. Because of this accident and the case study, it is now known that the amygdala is what processes negative emotions like fear and anger. Another famous case study is that of patient H. M., who had part of his hippocampus removed to prevent him from having seizures (Goulish, 2013). As a result of his surgery, his seizures were controlled, but he could not form any new memories (anterograde amnesia). Due to the learning that occurred with patient H. M., scientists learned that the part of the brain called the hippocampus is vital for memory formation and retention.

    There are many more famous case studies within psychology that you can read about if you are interested. Do you think that you might want to do something like this for your research? Who would you study? Why would they be of interest to you? What would make them original or unique in some way that would justify conducting a case study?

    In addition to case studies, there is another method of descriptive research called the
    _archival research approach_. Here, the researcher examines prior records of existing data, such as statistics that have been published by the government on a topic, or other historical artifacts such as pictures, documents, or even clothes (Gravetter & Foranzo, 2018). Something that is representative of a historical period would be an excellent example here. An important question to consider – particularly today – is there data you could use for your topic? You might be surprised to learn that there is an abundance of research available for you to review and analyze if you have interest that you can gain access to through publicly available datasets. Ask your professor for more information about this if you are interested, and review the archives to the NCU SSBS 2020 Research Conference for more discussion on just this topic!

    References

    Brogaard, B. (2017, July 10). The feral child nicknamed Genie.
    _Psychology Today_.

    Goulish, M. (2013). “A clear day and no memories”: Neurology, philosophy, and analogy in Kerry Tribe’s H.M.
    _Art Journal, 72_(3), 12–29.

    Gravetter, F. J., & Forzano, L. B. (2018).
    _Research methods for the behavioral sciences_ (6th ed.). Cengage Learning.

    Guidotti, T. L. (2012). Phineas Gage and his frontal lobe-The “American Crowbar case”.
    _Archives of Environmental and Occupational Health, 67_(4), 249-250.

    INTELECOM (Producer). (2011).
    _Western Electric Hawthorne studies: Results and conclusions_ [Video file]. Films on Demand.

    Sulloway, F. (December, 2005). The evolution of Charles Darwin.
    _Smithsonian Magazine_.

    **Assignment**

    Select one of the descriptive/observational approaches to research that you read about this week. Then, describe and detail this approach, and prepare a written assessment to discuss how you might use this approach to explore a topic of interest.

    Be sure to address the following:

    · Explain why you selected this method to study your chosen topic of interest.

    · Interpret the strengths and weaknesses of this approach.

    · Indicate what you might do to work around these weaknesses.

    · Verify whether this approach is more aligned with a qualitative or a quantitative approach to research, and then explain why.

    Next, identify and explain at least one other descriptive/observational approach you might consider using when researching your topic, describe the strengths and weaknesses of this approach, what you might do to work around weaknesses, and why you would want to use it to explore your topic further. Determine whether this design is more in line with a qualitative or a quantitative approach to research, and then explain why.

    Include the key similarities and differences between the two descriptive/observational approaches in a chart within your paper. You may also present this information as a graphic or other visual aid.

    Length: 5-7 pages, including chart or graphic, but not including title and reference pages

    References: Include a minimum of 3 scholarly resources.

    Your assignment should demonstrate thoughtful consideration of the ideas and concepts presented in the course by providing new thoughts and insights relating directly to this topic. Your response should reflect scholarly writing and current APA standards

    **Feedback from week 4:**

    You demonstrate a strong understanding of the different types of research questions as well as some of the methods that we use to answer each different type. As you move forward in weeks 5 and 6, you will explore these methods in more detail.

    In week 5, you will explore descriptive and observational methods that may be used to answer either descriptive or associative research questions, so choose one of the questions below and identify that question in the week 5 assignment before discussing two descriptive or observational methods that you may use to answer it.

    Descriptive: What is the average happiness level among married versus unmarried adults aged

    30 to 50?

    Associative: Is there a correlation between marital status and reported happiness levels among adults aged 30 to 50?

    **## Week5instructions.docx**

    **Observational/Descriptive Research**

    This week, you will learn more about the descriptive research methods scientists use to answer research questions that pertain to value or worth or how much of some variable is present. While reading about these different methods, begin to think more about how you might use each of these approaches with your specific research topic of interest.

    Generally, observational or descriptive research is the simplest and easiest research design to use. With this type of research design, you are simply observing or describing observable behaviors. The design itself is entirely ‘hands-off’, meaning you are simply making a note of what occurs naturally, without any intervention on the part of the researcher (Gravetter & Forzano, 2018). You might have video and audiotapes to review when using this approach as a way to be less obvious to participants.

    There are three basic types of descriptive research methods that psychologists frequently use, and these are
    _naturalistic observation, surveys,_ and
    _case studies_. In this week’s lesson, you will learn about each of these descriptive/observational research methods, along with the strengths and weaknesses of each approach.

    _Naturalistic observation_ is the descriptive approach Darwin used when he developed his theory of evolution while cruising in the
    _Beagle_(the name of his ship) in the Galapagos Islands (Sulloway, 2005). He formulated his theory of natural selection and the concept of
    _survival of the fittest_ through the descriptive method of naturalistic observation
    _._

    When conducting naturalistic observation, it is important to take steps to ‘blend right in’, while at the same time carefully observe whatever it is that you are studying. Your presence should go unnoticed, and as a result, you will not cause any sort of change in the behavior of the subjects you are observing. With naturalistic observation, you are trying to observe your subjects without making them aware that you are doing so. This is important to obtain a clearer picture of the truth or what is really happening. In other words, the
    _normal_ or
    _natural_ behavior of the participant. Otherwise, if they notice you are watching and paying attention, you may start to see noticeable changes in their behavior that do not reflect what they usually do. This is something called
    _subject reactivity_, and it is what you want to avoid when using naturalistic observation as the participant behavior is no longer ‘natural’ (Gravetter & Foranzo, 2018). While you might not think that others' mere presence can change or influence someone’s behavior, you will be surprised to learn that it can make a huge difference.

    The famous Hawthorne studies is perhaps one of the clearest examples of the issue of
    _subject reactivity,_ with naturalistic observation as the research method (Intellicom, 2011). With this landmark study, scientists were interested in determining whether or not the lighting that was being used in the factory would make a difference in worker productivity. So, they went in and periodically changed the lighting in the workplace. They did so by climbing up on ladders and changing the light bulbs during working hours when the workers were present. Interestingly enough, they found that these changes led to increases in productivity for all employees, regardless of the lighting itself. They eventually realized that it was the attention they were giving the workers that led to this improved performance, not the lighting. In other words, the fact that someone was paying attention to them is what caused the change in the behavior to occur. This had nothing whatsoever to do with the lighting! This is something for you to consider when using naturalistic observation as your descriptive research method. For example, in the Hawthorne studies, it is hypothesized that if the researchers had entered at night when the employees were not there, it most likely would have had no effect on their productivity. No changes in the employee behaviors would be evident. Thankfully, however, this was not the case, and a lot was learned about research subjects and participant reactivity as a result of this famous study.

    It is also important to remember with naturalistic observation, you can only study behaviors that are directly observable, meaning behaviors you can see or hear (Gravetter & Foranzo, 2018). You can not study a subject’s feelings, attitudes, values, or beliefs. This is a definite strength of the naturalistic observation design, for it is much more scientific and objective. However, at the same time, it is also a weakness in that you are limited to directly observable behaviors
    _only_. What might you do if you want to explore an individual's attitudes, beliefs, or feelings? You could opt to use a different descriptive method called a
    _survey_.

    _Surveys_ are also considered a descriptive approach to research for they allow the researcher to explore more subjective inner behaviors like a participant’s attitudes, beliefs, or values. In other words, it includes their thoughts and feelings, which are not directly observable. While this is a definite strength to the use of the survey research method, there are problems with this approach as well. More specifically, people will frequently lie or try to ‘look good’ to the researcher – even when surveys are anonymous. This is something called
    _social desirability_, and it is a genuine concern when using surveys. This issue is particularly relevant when the topic is a sensitive one (e.g., asking if they have ever engaged in illegal behavior). With surveys, researchers will typically provide participants with a statement of some sort, and they will then be asked to assess their level of agreement on a Likert-type scale of 1 to 5, or some other scale. Surveys
    are a popular research method because they are easy to use and relatively effective in assessing an individual’s inner behaviors.

    The last method of descriptive or observational research included in this week’s lesson is called a
    _case study_. A case study is a more in-depth exploration of a single subject, and it is typically only used when you have an individual who is different or unique in some way (Gravetter & Foranzo, 2018). For example, Genie the Wild Child's case is a very famous case study about a young girl who was kept isolated from the world for the first 12 years of her life (Broggard, 2017). Because of this isolation, she basically had no language development. As a result of the research on
    _Genie_, scientists came to realize that language development must occur during a critical time of overall childhood development. Otherwise, it will be delayed and difficult to obtain.

    Another famous case study includes that of Phineas Gage, the man with the railroad tine through his skull who lived but experienced significant changes in his personality due to his injury (Guidotti, 2012). Even though he lived to talk about it, he would often go into fits of rage because of the damage to his brain's amygdala. Because of this accident and the case study, it is now known that the amygdala is what processes negative emotions like fear and anger. Another famous case study is that of patient H. M., who had part of his hippocampus removed to prevent him from having seizures (Goulish, 2013). As a result of his surgery, his seizures were controlled, but he could not form any new memories (anterograde amnesia). Due to the learning that occurred with patient H. M., scientists learned that the part of the brain called the hippocampus is vital for memory formation and retention.

    There are many more famous case studies within psychology that you can read about if you are interested. Do you think that you might want to do something like this for your research? Who would you study? Why would they be of interest to you? What would make them original or unique in some way that would justify conducting a case study?

    In addition to case studies, there is another method of descriptive research called the
    _archival research approach_. Here, the researcher examines prior records of existing data, such as statistics that have been published by the government on a topic, or other historical artifacts such as pictures, documents, or even clothes (Gravetter & Foranzo, 2018). Something that is representative of a historical period would be an excellent example here. An important question to consider – particularly today – is there data you could use for your topic? You might be surprised to learn that there is an abundance of research available for you to review and analyze if you have interest that you can gain access to through publicly available datasets. Ask your professor for more information about this if you are interested, and review the archives to the NCU SSBS 2020 Research Conference for more discussion on just this topic!

    References

    Brogaard, B. (2017, July 10). The feral child nicknamed Genie.
    _Psychology Today_.

    Goulish, M. (2013). “A clear day and no memories”: Neurology, philosophy, and analogy in Kerry Tribe’s H.M.
    _Art Journal, 72_(3), 12–29.

    Gravetter, F. J., & Forzano, L. B. (2018).
    _Research methods for the behavioral sciences_ (6th ed.). Cengage Learning.

    Guidotti, T. L. (2012). Phineas Gage and his frontal lobe-The “American Crowbar case”.
    _Archives of Environmental and Occupational Health, 67_(4), 249-250.

    INTELECOM (Producer). (2011).
    _Western Electric Hawthorne studies: Results and conclusions_ [Video file]. Films on Demand.

    Sulloway, F. (December, 2005). The evolution of Charles Darwin.
    _Smithsonian Magazine_.

    **Assignment**

    Select one of the descriptive/observational approaches to research that you read about this week. Then, describe and detail this approach, and prepare a written assessment to discuss how you might use this approach to explore a topic of interest.

    Be sure to address the following:

    · Explain why you selected this method to study your chosen topic of interest.

    · Interpret the strengths and weaknesses of this approach.

    · Indicate what you might do to work around these weaknesses.

    · Verify whether this approach is more aligned with a qualitative or a quantitative approach to research, and then explain why.

    Next, identify and explain at least one other descriptive/observational approach you might consider using when researching your topic, describe the strengths and weaknesses of this approach, what you might do to work around weaknesses, and why you would want to use it to explore your topic further. Determine whether this design is more in line with a qualitative or a quantitative approach to research, and then explain why.

    Include the key similarities and differences between the two descriptive/observational approaches in a chart within your paper. You may also present this information as a graphic or other visual aid.

    Length: 5-7 pages, including chart or graphic, but not including title and reference pages

    References: Include a minimum of 3 scholarly resources.

    Your assignment should demonstrate thoughtful consideration of the ideas and concepts presented in the course by providing new thoughts and insights relating directly to this topic. Your response should reflect scholarly writing and current APA standards

    **Feedback from week 4:**

    You demonstrate a strong understanding of the different types of research questions as well as some of the methods that we use to answer each different type. As you move forward in weeks 5 and 6, you will explore these methods in more detail.

    In week 5, you will explore descriptive and observational methods that may be used to answer either descriptive or associative research questions, so choose one of the questions below and identify that question in the week 5 assignment before discussing two descriptive or observational methods that you may use to answer it.

    Descriptive: What is the average happiness level among married versus unmarried adults aged

    30 to 50?

    Associative: Is there a correlation between marital status and reported happiness levels among adults aged 30 to 50?

    **## Week5resources.docx**

    ·
    **“A Clear Day and No Memories”: Neurology, Philosophy, and Analogy in Kerry Tribe’s H.M.**

    Goulish, M. (2013). “A clear day and no memories”: Neurology, philosophy, and analogy in Kerry Tribe’s H.M.
    _Art Journal, 72_(3), 12–29.

    ·
    [**Phineas Gage and his Frontal Lobe-The “American Crowbar Case”**](https://search.ebscohost.com/login.aspx?authtype=shib&custid=natuniv&direct=true&db=mdc&AN=23074983&site=eds-live)

    Guidotti, T. L. (2012). Phineas Gage and his frontal lobe-The “American Crowbar case”.
    _Archives of Environmental and Occupational Health, 67_(4), 249-250.

    ·
    [**The Evolution of Charles Darwin**](https://www.smithsonianmag.com/science-nature/the-evolution-of-charles-darwin-110234034/)

    Sulloway, F. (December, 2005).
    _The evolution of Charles Darwin._ Smithsonian Magazine.

    ·
    [**The Feral Child Nicknamed Genie**](https://www.psychologytoday.com/us/blog/the-superhuman-mind/201707/the-feral-child-nicknamed-genie)

    Brogaard, B. (2017, July 10). The feral child nicknamed Genie.
    _Psychology Today._

    **## Week5instructions.docx**

    **Observational/Descriptive Research**

    This week, you will learn more about the descriptive research methods scientists use to answer research questions that pertain to value or worth or how much of some variable is present. While reading about these different methods, begin to think more about how you might use each of these approaches with your specific research topic of interest.

    Generally, observational or descriptive research is the simplest and easiest research design to use. With this type of research design, you are simply observing or describing observable behaviors. The design itself is entirely ‘hands-off’, meaning you are simply making a note of what occurs naturally, without any intervention on the part of the researcher (Gravetter & Forzano, 2018). You might have video and audiotapes to review when using this approach as a way to be less obvious to participants.

    There are three basic types of descriptive research methods that psychologists frequently use, and these are
    _naturalistic observation, surveys,_ and
    _case studies_. In this week’s lesson, you will learn about each of these descriptive/observational research methods, along with the strengths and weaknesses of each approach.

    _Naturalistic observation_ is the descriptive approach Darwin used when he developed his theory of evolution while cruising in the
    _Beagle_(the name of his ship) in the Galapagos Islands (Sulloway, 2005). He formulated his theory of natural selection and the concept of
    _survival of the fittest_ through the descriptive method of naturalistic observation
    _._

    When conducting naturalistic observation, it is important to take steps to ‘blend right in’, while at the same time carefully observe whatever it is that you are studying. Your presence should go unnoticed, and as a result, you will not cause any sort of change in the behavior of the subjects you are observing. With naturalistic observation, you are trying to observe your subjects without making them aware that you are doing so. This is important to obtain a clearer picture of the truth or what is really happening. In other words, the
    _normal_ or
    _natural_ behavior of the participant. Otherwise, if they notice you are watching and paying attention, you may start to see noticeable changes in their behavior that do not reflect what they usually do. This is something called
    _subject reactivity_, and it is what you want to avoid when using naturalistic observation as the participant behavior is no longer ‘natural’ (Gravetter & Foranzo, 2018). While you might not think that others' mere presence can change or influence someone’s behavior, you will be surprised to learn that it can make a huge difference.

    The famous Hawthorne studies is perhaps one of the clearest examples of the issue of
    _subject reactivity,_ with naturalistic observation as the research method (Intellicom, 2011). With this landmark study, scientists were interested in determining whether or not the lighting that was being used in the factory would make a difference in worker productivity. So, they went in and periodically changed the lighting in the workplace. They did so by climbing up on ladders and changing the light bulbs during working hours when the workers were present. Interestingly enough, they found that these changes led to increases in productivity for all employees, regardless of the lighting itself. They eventually realized that it was the attention they were giving the workers that led to this improved performance, not the lighting. In other words, the fact that someone was paying attention to them is what caused the change in the behavior to occur. This had nothing whatsoever to do with the lighting! This is something for you to consider when using naturalistic observation as your descriptive research method. For example, in the Hawthorne studies, it is hypothesized that if the researchers had entered at night when the employees were not there, it most likely would have had no effect on their productivity. No changes in the employee behaviors would be evident. Thankfully, however, this was not the case, and a lot was learned about research subjects and participant reactivity as a result of this famous study.

    It is also important to remember with naturalistic observation, you can only study behaviors that are directly observable, meaning behaviors you can see or hear (Gravetter & Foranzo, 2018). You can not study a subject’s feelings, attitudes, values, or beliefs. This is a definite strength of the naturalistic observation design, for it is much more scientific and objective. However, at the same time, it is also a weakness in that you are limited to directly observable behaviors
    _only_. What might you do if you want to explore an individual's attitudes, beliefs, or feelings? You could opt to use a different descriptive method called a
    _survey_.

    _Surveys_ are also considered a descriptive approach to research for they allow the researcher to explore more subjective inner behaviors like a participant’s attitudes, beliefs, or values. In other words, it includes their thoughts and feelings, which are not directly observable. While this is a definite strength to the use of the survey research method, there are problems with this approach as well. More specifically, people will frequently lie or try to ‘look good’ to the researcher – even when surveys are anonymous. This is something called
    _social desirability_, and it is a genuine concern when using surveys. This issue is particularly relevant when the topic is a sensitive one (e.g., asking if they have ever engaged in illegal behavior). With surveys, researchers will typically provide participants with a statement of some sort, and they will then be asked to assess their level of agreement on a Likert-type scale of 1 to 5, or some other scale. Surveys
    are a popular research method because they are easy to use and relatively effective in assessing an individual’s inner behaviors.

    The last method of descriptive or observational research included in this week’s lesson is called a
    _case study_. A case study is a more in-depth exploration of a single subject, and it is typically only used when you have an individual who is different or unique in some way (Gravetter & Foranzo, 2018). For example, Genie the Wild Child's case is a very famous case study about a young girl who was kept isolated from the world for the first 12 years of her life (Broggard, 2017). Because of this isolation, she basically had no language development. As a result of the research on
    _Genie_, scientists came to realize that language development must occur during a critical time of overall childhood development. Otherwise, it will be delayed and difficult to obtain.

    Another famous case study includes that of Phineas Gage, the man with the railroad tine through his skull who lived but experienced significant changes in his personality due to his injury (Guidotti, 2012). Even though he lived to talk about it, he would often go into fits of rage because of the damage to his brain's amygdala. Because of this accident and the case study, it is now known that the amygdala is what processes negative emotions like fear and anger. Another famous case study is that of patient H. M., who had part of his hippocampus removed to prevent him from having seizures (Goulish, 2013). As a result of his surgery, his seizures were controlled, but he could not form any new memories (anterograde amnesia). Due to the learning that occurred with patient H. M., scientists learned that the part of the brain called the hippocampus is vital for memory formation and retention.

    There are many more famous case studies within psychology that you can read about if you are interested. Do you think that you might want to do something like this for your research? Who would you study? Why would they be of interest to you? What would make them original or unique in some way that would justify conducting a case study?

    In addition to case studies, there is another method of descriptive research called the
    _archival research approach_. Here, the researcher examines prior records of existing data, such as statistics that have been published by the government on a topic, or other historical artifacts such as pictures, documents, or even clothes (Gravetter & Foranzo, 2018). Something that is representative of a historical period would be an excellent example here. An important question to consider – particularly today – is there data you could use for your topic? You might be surprised to learn that there is an abundance of research available for you to review and analyze if you have interest that you can gain access to through publicly available datasets. Ask your professor for more information about this if you are interested, and review the archives to the NCU SSBS 2020 Research Conference for more discussion on just this topic!

    References

    Brogaard, B. (2017, July 10). The feral child nicknamed Genie.
    _Psychology Today_.

    Goulish, M. (2013). “A clear day and no memories”: Neurology, philosophy, and analogy in Kerry Tribe’s H.M.
    _Art Journal, 72_(3), 12–29.

    Gravetter, F. J., & Forzano, L. B. (2018).
    _Research methods for the behavioral sciences_ (6th ed.). Cengage Learning.

    Guidotti, T. L. (2012). Phineas Gage and his frontal lobe-The “American Crowbar case”.
    _Archives of Environmental and Occupational Health, 67_(4), 249-250.

    INTELECOM (Producer). (2011).
    _Western Electric Hawthorne studies: Results and conclusions_ [Video file]. Films on Demand.

    Sulloway, F. (December, 2005). The evolution of Charles Darwin.
    _Smithsonian Magazine_.

    **Assignment**

    Select one of the descriptive/observational approaches to research that you read about this week. Then, describe and detail this approach, and prepare a written assessment to discuss how you might use this approach to explore a topic of interest.

    Be sure to address the following:

    · Explain why you selected this method to study your chosen topic of interest.

    · Interpret the strengths and weaknesses of this approach.

    · Indicate what you might do to work around these weaknesses.

    · Verify whether this approach is more aligned with a qualitative or a quantitative approach to research, and then explain why.

    Next, identify and explain at least one other descriptive/observational approach you might consider using when researching your topic, describe the strengths and weaknesses of this approach, what you might do to work around weaknesses, and why you would want to use it to explore your topic further. Determine whether this design is more in line with a qualitative or a quantitative approach to research, and then explain why.

    Include the key similarities and differences between the two descriptive/observational approaches in a chart within your paper. You may also present this information as a graphic or other visual aid.

    Length: 5-7 pages, including chart or graphic, but not including title and reference pages

    References: Include a minimum of 3 scholarly resources.

    Your assignment should demonstrate thoughtful consideration of the ideas and concepts presented in the course by providing new thoughts and insights relating directly to this topic. Your response should reflect scholarly writing and current APA standards

    **Feedback from week 4:**

    You demonstrate a strong understanding of the different types of research questions as well as some of the methods that we use to answer each different type. As you move forward in weeks 5 and 6, you will explore these methods in more detail.

    In week 5, you will explore descriptive and observational methods that may be used to answer either descriptive or associative research questions, so choose one of the questions below and identify that question in the week 5 assignment before discussing two descriptive or observational methods that you may use to answer it.

    Descriptive: What is the average happiness level among married versus unmarried adults aged

    30 to 50?

    Associative: Is there a correlation between marital status and reported happiness levels among adults aged 30 to 50?

    **## Week5resources.docx**

    ·
    **“A Clear Day and No Memories”: Neurology, Philosophy, and Analogy in Kerry Tribe’s H.M.**

    Goulish, M. (2013). “A clear day and no memories”: Neurology, philosophy, and analogy in Kerry Tribe’s H.M.
    _Art Journal, 72_(3), 12–29.

    ·
    [**Phineas Gage and his Frontal Lobe-The “American Crowbar Case”**](https://search.ebscohost.com/login.aspx?authtype=shib&custid=natuniv&direct=true&db=mdc&AN=23074983&site=eds-live)

    Guidotti, T. L. (2012). Phineas Gage and his frontal lobe-The “American Crowbar case”.
    _Archives of Environmental and Occupational Health, 67_(4), 249-250.

    ·
    [**The Evolution of Charles Darwin**](https://www.smithsonianmag.com/science-nature/the-evolution-of-charles-darwin-110234034/)

    Sulloway, F. (December, 2005).
    _The evolution of Charles Darwin._ Smithsonian Magazine.

    ·
    [**The Feral Child Nicknamed Genie**](https://www.psychologytoday.com/us/blog/the-superhuman-mind/201707/the-feral-child-nicknamed-genie)

    Brogaard, B. (2017, July 10). The feral child nicknamed Genie.
    _Psychology Today._

    **## Week5instructions.docx**

    **Observational/Descriptive Research**

    This week, you will learn more about the descriptive research methods scientists use to answer research questions that pertain to value or worth or how much of some variable is present. While reading about these different methods, begin to think more about how you might use each of these approaches with your specific research topic of interest.

    Generally, observational or descriptive research is the simplest and easiest research design to use. With this type of research design, you are simply observing or describing observable behaviors. The design itself is entirely ‘hands-off’, meaning you are simply making a note of what occurs naturally, without any intervention on the part of the researcher (Gravetter & Forzano, 2018). You might have video and audiotapes to review when using this approach as a way to be less obvious to participants.

    There are three basic types of descriptive research methods that psychologists frequently use, and these are
    _naturalistic observation, surveys,_ and
    _case studies_. In this week’s lesson, you will learn about each of these descriptive/observational research methods, along with the strengths and weaknesses of each approach.

    _Naturalistic observation_ is the descriptive approach Darwin used when he developed his theory of evolution while cruising in the
    _Beagle_(the name of his ship) in the Galapagos Islands (Sulloway, 2005). He formulated his theory of natural selection and the concept of
    _survival of the fittest_ through the descriptive method of naturalistic observation
    _._

    When conducting naturalistic observation, it is important to take steps to ‘blend right in’, while at the same time carefully observe whatever it is that you are studying. Your presence should go unnoticed, and as a result, you will not cause any sort of change in the behavior of the subjects you are observing. With naturalistic observation, you are trying to observe your subjects without making them aware that you are doing so. This is important to obtain a clearer picture of the truth or what is really happening. In other words, the
    _normal_ or
    _natural_ behavior of the participant. Otherwise, if they notice you are watching and paying attention, you may start to see noticeable changes in their behavior that do not reflect what they usually do. This is something called
    _subject reactivity_, and it is what you want to avoid when using naturalistic observation as the participant behavior is no longer ‘natural’ (Gravetter & Foranzo, 2018). While you might not think that others' mere presence can change or influence someone’s behavior, you will be surprised to learn that it can make a huge difference.

    The famous Hawthorne studies is perhaps one of the clearest examples of the issue of
    _subject reactivity,_ with naturalistic observation as the research method (Intellicom, 2011). With this landmark study, scientists were interested in determining whether or not the lighting that was being used in the factory would make a difference in worker productivity. So, they went in and periodically changed the lighting in the workplace. They did so by climbing up on ladders and changing the light bulbs during working hours when the workers were present. Interestingly enough, they found that these changes led to increases in productivity for all employees, regardless of the lighting itself. They eventually realized that it was the attention they were giving the workers that led to this improved performance, not the lighting. In other words, the fact that someone was paying attention to them is what caused the change in the behavior to occur. This had nothing whatsoever to do with the lighting! This is something for you to consider when using naturalistic observation as your descriptive research method. For example, in the Hawthorne studies, it is hypothesized that if the researchers had entered at night when the employees were not there, it most likely would have had no effect on their productivity. No changes in the employee behaviors would be evident. Thankfully, however, this was not the case, and a lot was learned about research subjects and participant reactivity as a result of this famous study.

    It is also important to remember with naturalistic observation, you can only study behaviors that are directly observable, meaning behaviors you can see or hear (Gravetter & Foranzo, 2018). You can not study a subject’s feelings, attitudes, values, or beliefs. This is a definite strength of the naturalistic observation design, for it is much more scientific and objective. However, at the same time, it is also a weakness in that you are limited to directly observable behaviors
    _only_. What might you do if you want to explore an individual's attitudes, beliefs, or feelings? You could opt to use a different descriptive method called a
    _survey_.

    _Surveys_ are also considered a descriptive approach to research for they allow the researcher to explore more subjective inner behaviors like a participant’s attitudes, beliefs, or values. In other words, it includes their thoughts and feelings, which are not directly observable. While this is a definite strength to the use of the survey research method, there are problems with this approach as well. More specifically, people will frequently lie or try to ‘look good’ to the researcher – even when surveys are anonymous. This is something called
    _social desirability_, and it is a genuine concern when using surveys. This issue is particularly relevant when the topic is a sensitive one (e.g., asking if they have ever engaged in illegal behavior). With surveys, researchers will typically provide participants with a statement of some sort, and they will then be asked to assess their level of agreement on a Likert-type scale of 1 to 5, or some other scale. Surveys
    are a popular research method because they are easy to use and relatively effective in assessing an individual’s inner behaviors.

    The last method of descriptive or observational research included in this week’s lesson is called a
    _case study_. A case study is a more in-depth exploration of a single subject, and it is typically only used when you have an individual who is different or unique in some way (Gravetter & Foranzo, 2018). For example, Genie the Wild Child's case is a very famous case study about a young girl who was kept isolated from the world for the first 12 years of her life (Broggard, 2017). Because of this isolation, she basically had no language development. As a result of the research on
    _Genie_, scientists came to realize that language development must occur during a critical time of overall childhood development. Otherwise, it will be delayed and difficult to obtain.

    Another famous case study includes that of Phineas Gage, the man with the railroad tine through his skull who lived but experienced significant changes in his personality due to his injury (Guidotti, 2012). Even though he lived to talk about it, he would often go into fits of rage because of the damage to his brain's amygdala. Because of this accident and the case study, it is now known that the amygdala is what processes negative emotions like fear and anger. Another famous case study is that of patient H. M., who had part of his hippocampus removed to prevent him from having seizures (Goulish, 2013). As a result of his surgery, his seizures were controlled, but he could not form any new memories (anterograde amnesia). Due to the learning that occurred with patient H. M., scientists learned that the part of the brain called the hippocampus is vital for memory formation and retention.

    There are many more famous case studies within psychology that you can read about if you are interested. Do you think that you might want to do something like this for your research? Who would you study? Why would they be of interest to you? What would make them original or unique in some way that would justify conducting a case study?

    In addition to case studies, there is another method of descriptive research called the
    _archival research approach_. Here, the researcher examines prior records of existing data, such as statistics that have been published by the government on a topic, or other historical artifacts such as pictures, documents, or even clothes (Gravetter & Foranzo, 2018). Something that is representative of a historical period would be an excellent example here. An important question to consider – particularly today – is there data you could use for your topic? You might be surprised to learn that there is an abundance of research available for you to review and analyze if you have interest that you can gain access to through publicly available datasets. Ask your professor for more information about this if you are interested, and review the archives to the NCU SSBS 2020 Research Conference for more discussion on just this topic!

    References

    Brogaard, B. (2017, July 10). The feral child nicknamed Genie.
    _Psychology Today_.

    Goulish, M. (2013). “A clear day and no memories”: Neurology, philosophy, and analogy in Kerry Tribe’s H.M.
    _Art Journal, 72_(3), 12–29.

    Gravetter, F. J., & Forzano, L. B. (2018).
    _Research methods for the behavioral sciences_ (6th ed.). Cengage Learning.

    Guidotti, T. L. (2012). Phineas Gage and his frontal lobe-The “American Crowbar case”.
    _Archives of Environmental and Occupational Health, 67_(4), 249-250.

    INTELECOM (Producer). (2011).
    _Western Electric Hawthorne studies: Results and conclusions_ [Video file]. Films on Demand.

    Sulloway, F. (December, 2005). The evolution of Charles Darwin.
    _Smithsonian Magazine_.

    **Assignment**

    Select one of the descriptive/observational approaches to research that you read about this week. Then, describe and detail this approach, and prepare a written assessment to discuss how you might use this approach to explore a topic of interest.

    Be sure to address the following:

    · Explain why you selected this method to study your chosen topic of interest.

    · Interpret the strengths and weaknesses of this approach.

    · Indicate what you might do to work around these weaknesses.

    · Verify whether this approach is more aligned with a qualitative or a quantitative approach to research, and then explain why.

    Next, identify and explain at least one other descriptive/observational approach you might consider using when researching your topic, describe the strengths and weaknesses of this approach, what you might do to work around weaknesses, and why you would want to use it to explore your topic further. Determine whether this design is more in line with a qualitative or a quantitative approach to research, and then explain why.

    Include the key similarities and differences between the two descriptive/observational approaches in a chart within your paper. You may also present this information as a graphic or other visual aid.

    Length: 5-7 pages, including chart or graphic, but not including title and reference pages

    References: Include a minimum of 3 scholarly resources.

    Your assignment should demonstrate thoughtful consideration of the ideas and concepts presented in the course by providing new thoughts and insights relating directly to this topic. Your response should reflect scholarly writing and current APA standards

    **Feedback from week 4:**

    You demonstrate a strong understanding of the different types of research questions as well as some of the methods that we use to answer each different type. As you move forward in weeks 5 and 6, you will explore these methods in more detail.

    In week 5, you will explore descriptive and observational methods that may be used to answer either descriptive or associative research questions, so choose one of the questions below and identify that question in the week 5 assignment before discussing two descriptive or observational methods that you may use to answer it.

    Descriptive: What is the average happiness level among married versus unmarried adults aged

    30 to 50?

    Associative: Is there a correlation between marital status and reported happiness levels among adults aged 30 to 50?

    – 1
    – 2