Pervasive But Problematic: How Generative AI Is Disrupting Academia

Dominating headlines since late 2022, the generative AI system ChatGPT, has rapidly become one of the most controversial and fastest-growing consumer applications in history [1]. Capable of composing Shakespearean sonnets with hip-hop lyrics, drafting manuscripts with key points and strong counterarguments, or creating academic blogs worthy of publication, ChatGPT offers unrivalled potential to automize tasks and generate large bodies of text at lightning speed [2].

Original image generated using DALL·E text to image AI generator. Available from: https://openai.com/dall-e-2/

ChatGPT is a sophisticated language model that responds to user requests in ways that appear intuitive and conversational [3]. The model is built upon swathes of information obtained from the internet, 300 million words to be precise [4]. ChatGPT works by forming connections between data to reveal patterns of information that align with user prompts [5]. As a language model, ChatGPT has the ability to remember threads of information, enabling users to ask follow-up or clarifying questions. It is this personalized interactive dialogue that elevates it above traditional search engine models.

Unsurprisingly, generative AI has amassed a strong army of followers eager to monopolise on its efficient functionalities: 100 million people conversed with the chatbot in January alone [1].

But what might the lure of working smarter, not harder mean in academia?

Perilous Publishing, Or Powerful Penmanship

No longer a whisper shared between hushed sororities, generative AI like ChatGPT has become a powerful force proudly employed by professors and pupils alike. However, despite its popularity, uptake is not unanimous. Academics are divided.

With the ability to generate work at the touch of a button, users risk being led down a perilous path towards plagiarism, and having their development stifled. The clear threat to academic integrity and original thought is sending many into a state of panic [6–8]. Editors of scientific journals are also having to wrestle with publishing ethics, as ChatGPT is increasingly being cited as a co-author [9].

But, despite its outward looking proficiency, the generative AI model has a number of particularly unnerving limitations. In the words of OpenAI, ChatGPT’s parent company, the software “will occasionally make up facts or ‘hallucinate’ outputs, [that] may be inaccurate, untruthful, and otherwise misleading” [5].

Available from: https://chat.openai.com/chat

The rise of generative AI shines a spotlight on a troublesome issue in academia: the exchange of papers for grades. Whilst finished articles are necessary, when product triumphs over process, valuable lessons found in the process of writing can be overlooked.

“This technology [generative AI] … cuts into the university’s core purpose of cultivating a thoughtful and critically engaged citizenry. If we can now all access sophisticated and original writing with a simple prompt, why require students to write at all?” [10]

Responsively, in an attempt to stem the flow of plagiarism and untruth, and protect creative thinking, some academics have enforced outright bans of generative AI systems [2].

Unethical AI

Academic integrity aside, ChatGPT’s capabilities are also undermined by moral and ethical concerns.

A recent Times Magazine exposé revealed that OpenAI outsources work to a firm in Kenya, whose staff are assigned the menial task of trawling through mountains of data, flagging harmful items to ensure that ChatGPT’s outputs are “safe for human consumption”. Data Enrichment Specialists earn less than $2/hour [2].

Moreover, generative AI propagates systemic biases by repurposing primarily westernised data in response to English-language prompts, created by tech-savvy users with easy access to IT. For some, the commercialization of more sophisticated platforms like ChatGPT Pro will also prove particularly exclusionary [10–13].

Embracing The Chatbot

However, vying in support of generative AI in academia, are those such as Associate Professor of Learning Enhancement at Edinburgh Napier University, Sam Illingworth, who state that it would be unrealistic and unrepresentative of future workplaces if students did not learn to use these technologies. Illingworth and others call for a shift from albeit valid concerns around insidious plagiarism (OpenAI’s own plagiarism detector tool is highly inaccurate, with a 26% success rate [11]) toward embracing the opportunities as a chance to reshape pedagogy [4].

Methods for teaching and assessment are having to be reexamined, with some suggesting that a return to traditional methods, such as impromptu oral exams, personal reflections or in-person written assignments, may prove effective against a proliferation of AI generated work [12,13].

Generative AI chatbots also have the potential to become a teacher’s best friend [14]. Automating grading rubrics or assisting with lesson planning might offer a much-needed morale boost to a professional body whose expertise is being somewhat jeopardized by the emergent technology. And despite rumors of existential threat [15,16], generative AI, for now at least, poses no immediate risk of replacing human educators; empathy and creativity are among unique human qualities proving tricky to manufacture from binary code.

The Future Is Unknown

Much like other technologies that have emerged from Sisyphean cycles of innovation (think Casio graphing calculator or Mac OS), ChatGPT and fellow generative AI chatbots have the potential to transform the face of education [17].

As the AI arms race marches on at quickening pace, with companies delivering a daily bombardment of upgrades and functionalities, it is impossible to predict who, or what, might benefit or become a casualty to automation in academia. The story of AI in academia remains unwritten, but as the indelible mark left by ChatGPT suggests, it is certain to deliver a compelling narrative.

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References:

1.         Hu K. ChatGPT sets record for fastest-growing user base – analyst note. Reuters [Internet]. 2023 Feb 2 [cited 2023 Feb 6]; Available from: https://www.reuters.com/technology/chatgpt-sets-record-fastest-growing-user-base-analyst-note-2023-02-01/

2.         Perrigo B. OpenAI Used Kenyan Workers on Less Than $2 Per Hour: Exclusive | Time [Internet]. 2023 [cited 2023 Feb 13]. Available from: https://time.com/6247678/openai-chatgpt-kenya-workers/

3.         OpenAi. ChatGPT: Optimizing Language Models for Dialogue [Internet]. OpenAI. 2022 [cited 2023 Feb 17]. Available from: https://openai.com/blog/chatgpt/

4.         Hughes A. ChatGPT: Everything you need to know about OpenAI’s GPT-3 tool [Internet]. BBC Science Focus Magazine. 2023 [cited 2023 Feb 6]. Available from: https://www.sciencefocus.com/future-technology/gpt-3/

5.         OpenAi. ChatGPT General FAQ [Internet]. 2023 [cited 2023 Feb 18]. Available from: https://help.openai.com/en/articles/6783457-chatgpt-general-faq

6.         Heidt A. ‘Arms race with automation’: professors fret about AI-generated coursework. Nature [Internet]. 2023 Jan 24 [cited 2023 Feb 6]; Available from: https://www.nature.com/articles/d41586-023-00204-z

7.         Kubacka T. “Publish-or-perish” and ChatGPT: a dangerous mix [Internet]. Lookalikes and Meanders. 2023 [cited 2023 Feb 6]. Available from: https://lookalikes.substack.com/p/publish-or-perish-and-chatgpt-a-dangerous

8.         Boyle K. A reason for the moral panic re AI in academia: in work, we learn prioritization of tasks, which higher ed doesn’t prize. Speed is crucial in work— it’s discouraged in school. Tools that encourage speed are bad for some established industries. Take note of who screams loudly. https://t.co/ot8YHh7H7b [Internet]. Twitter. 2023 [cited 2023 Feb 6]. Available from: https://twitter.com/KTmBoyle/status/1619384367637471234

9.         Stokel-Walker C. ChatGPT listed as author on research papers: many scientists disapprove. Nature [Internet]. 2023 Jan 18 [cited 2023 Feb 21];613(7945):620–1. Available from: https://www.nature.com/articles/d41586-023-00107-z

10.       Southworth J. Rethinking university writing pedagogy in a world of ChatGPT [Internet]. University Affairs. 2023 [cited 2023 Feb 18]. Available from: https://www.universityaffairs.ca/opinion/in-my-opinion/rethinking-university-writing-pedagogy-in-a-world-of-chatgpt/

11.       Wiggers K. OpenAI releases tool to detect AI-generated text, including from ChatGPT [Internet]. TechCrunch. 2023 [cited 2023 Feb 6]. Available from: https://techcrunch.com/2023/01/31/openai-releases-tool-to-detect-ai-generated-text-including-from-chatgpt/

12.       Nature Portfolio. A poll of @Nature readers about the use of AI chatbots in academia suggests that the resulting essays are still easy to flag, and it’s possible to amend existing policies and assignments to address their use. https://t.co/lHyPtEEb7F [Internet]. Twitter. 2023 [cited 2023 Feb 6]. Available from: https://twitter.com/NaturePortfolio/status/1619751476947046408

13.       Khatsenkova S. ChatGPT: Is it possible to spot AI-generated text? [Internet]. euronews. 2023 [cited 2023 Feb 6]. Available from: https://www.euronews.com/next/2023/01/19/chatgpt-is-it-possible-to-detect-ai-generated-text

14.       Roose K. Don’t Ban ChatGPT in Schools. Teach With It. The New York Times [Internet]. 2023 Jan 12 [cited 2023 Feb 21]; Available from: https://www.nytimes.com/2023/01/12/technology/chatgpt-schools-teachers.html

15.       Thorp HH. ChatGPT is fun, but not an author. Science [Internet]. 2023 Jan 27 [cited 2023 Feb 6];379(6630):313–313. Available from: https://www.science.org/doi/10.1126/science.adg7879

16.       Chow A, Perrigo B. The AI Arms Race Is On. Start Worrying | Time [Internet]. 2023 [cited 2023 Feb 18]. Available from: https://time.com/6255952/ai-impact-chatgpt-microsoft-google/

17.       Orben A. The Sisyphean Cycle of Technology Panics. Perspect Psychol Sci [Internet]. 2020 Sep 1 [cited 2023 Feb 6];15(5):1143–57. Available from: https://doi.org/10.1177/1745691620919372

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Susanna Martin BSc (Hons) is a Research Assistant at The Neuroscience Engagement and Smart Tech (NEST) lab.

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Designing for Dementia: Towards a Truly Universal Built Environment

The buildings and streets around us shape how we interact with the environment. How can we design cities that are equitable and accessible for people living with dementia?

The physical structures in which we live, work, and play constitute the built environment around us^[1]. Since we constantly interact with the built environment, architects must consider different needs and abilities in their designs to enable equitable access. This is called universal design^[2], and it can be seen all around us.

Take, for example, a crosswalk. In the image below, the sidewalk slopes down to provide wheelchair access. There are also tactile bumps to signify a crossing for people using a long cane. The walking person signal provides clear instructions for those who cannot hear the traffic slowing. All these features represent design decisions made to increase the usability of the crosswalk.

https://www.toronto.ca/services-payments/streets-parking-transportation/traffic-management/traffic-signals-street-signs/types-of-traffic-signals/accessible-pedestrian-signals/

Not Yet Universal

While designers have tried to create built environments that are universally accessible, they rarely consult people with lived experience of dementia in the design process. The result is cities and spaces that are confusing and inaccessible to those with dementia^[1,3–5].

The City of Vancouver exemplifies this disconnect in what they specify as “accessible street design”^[6]. Despite claiming to use the principles of universal design, the city’s specifications mainly focus on physical disabilities and neglect considerations for dementia. Further, dementia research tends to focus on social interactions and personal connections. Designers are simply unaware of the needs of those living with dementia^[4,7,8].

Work in the field of Environmental Gerontology – which considers the relationship between the environment, health, and aging – has made the issue clear: making the built environment more accessible can improve quality of life for people with dementia^[7]. How do we adapt our environments to better suit their needs?

Limited Work in Limited Spaces

To date, only a few small-scale research trials included people with dementia in the design process. One example is the Lepine-Versailles Garden in France, which took input from people living with dementia and their care partners. Dementia-specific features include clearly marked boundaries to the garden, and small enclosed spaces that help relieve anxiety and provide safety^[9]. These small spaces can provide a place for close, quiet social interactions, which become more relevant as dementia progresses and language skills diminish^[8].

Environmental interventions are also present in the psychogeriatric environment. One hospital in the Netherlands built custom handrails to help people living with dementia navigate more easily^[4]. For example, they made one handrail of wood and played bird noises to help residents find the garden.

Handrail with a bird located near the garden. Nearby speakers played bird chirping sounds. Reproduced from Ludden et al. (2019).

However, these findings are very limited – they apply to specific environments that are not representative of most people’s experiences with dementia. A majority of people with dementia live in their home, and they routinely navigate their environment by taking walks on their own^[3,5]. Increasingly, health research has emphasized the idea of ‘aging in place,’ suggesting that the number of people living at home with dementia will increase.

Design Principles for Dementia

So, what should dementia friendly environments actually look like? Mitchell and Burton studied the design principles that make environments accessible^[3,5]. Based on these design principles, they developed design strategies to help people living with dementia flourish in the built environment. These include:

• Small blocks laid out in an irregular grid with minimal crossroads and gently winding streets: this layout emphasises legibility, allowing people to identify where they need to go and avoid complicated crossroads.
• Varied urban form and architecture, with landmarks and visual cues: this makes different parts of a neighbourhood more distinct from each other, which can help with wayfinding and orienting.
• Mixed use buildings, including plenty of local services: this ensures people do not have to travel too far from their homes to access essential services (e.g., grocery store) and enables access without the need for driving or transiting.

These recommendations highlight the specific needs of people living with dementia that designers often overlook. For example, while cities designed on a grid are easy to navigate for most people, these grids are often repetitive and rely on numbered streets signs to navigate, making this design inaccessible to those with dementia.

From Ideas to Implementation: An Ethical Imperative

In summary, designers should prioritize the long-overlooked needs of people with dementia in their designs. Researchers have developed detailed recommendations for how to include dementia in universal design. Implementation is now the key.

With the global population aging, the number of people living with dementia is increasing. The focus on aging in place also means that many people will remain in their homes for longer and interact with the public environment (as opposed to specific dementia care facilities). It is therefore an ethical imperative that architects, city planners, and all other groups involved in the process of designing our built environment begin to consider the needs of people living with dementia.

Consulting people living with dementia during the design process is an opportunity to preserve their autonomy and dignity. This will require an overhaul of how we think about our built environment, and a shift towards truly universal design.

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References

1. Sturge, J., Nordin, S., Sussana Patil, D., Jones, A., Légaré, F., Elf, M., & Meijering, L. (2021). Features of the social and built environment that contribute to the well-being of people with dementia who live at home: A scoping review. Health & Place, 67, 102483. https://doi.org/10.1016/j.healthplace.2020.102483
2. Story, M. F. (1998). Maximizing Usability: The Principles of Universal Design. Assistive Technology, 10(1), 4–12. https://doi.org/10.1080/10400435.1998.10131955
3. Mitchell, L., & Burton, E. (2010). Designing Dementia‐Friendly Neighbourhoods: Helping People with Dementia to Get Out and About. Journal of Integrated Care, 18(6), 11–18. https://doi.org/10.5042/jic.2010.0647
4. Ludden, G. D. S., van Rompay, T. J. L., Niedderer, K., & Tournier, I. (2019). Environmental design for dementia care—Towards more meaningful experiences through design. Maturitas, 128, 10–16. https://doi.org/10.1016/j.maturitas.2019.06.011
5. Mitchell, L., & Burton, E. (2006). Neighbourhoods for life: Designing dementia‐friendly outdoor environments. Quality in Ageing and Older Adults, 7(1), 26–33. https://doi.org/10.1108/14717794200600005
6. Accessible Street Design. (n.d.). The City of Vancouver Engineering Services. Retrieved January 1, 2023, from https://vancouver.ca/files/cov/accessiblestreetdesign.pdf
7. Chrysikou, E., Tziraki, C., & Buhalis, D. (2018). Architectural hybrids for living across the lifespan: Lessons from dementia. The Service Industries Journal, 38(1–2), 4–26. https://doi.org/10.1080/02642069.2017.1365138
8. Van Steenwinkel, I., Van Audenhove, C., & Heylighen, A. (2019). Offering architects insights into experiences of living with dementia: A case study on orientation in space, time, and identity. Dementia, 18(2), 742–756. https://doi.org/10.1177/1471301217692905
9. Charras, K., Bébin, C., Laulier, V., Mabire, J.-B., & Aquino, J.-P. (2020). Designing dementia-friendly gardens: A workshop for landscape architects: Innovative Practice. Dementia, 19(7), 2504–2512. https://doi.org/10.1177/1471301218808609

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Grayden Zaleski is a Directed Studies Student under the supervision of Dr. Julie Robillard in the NEST Lab. He is pursuing a Bachelor of Science degree with a major in Behavioural Neuroscience and a Computer Science minor. His research interests include human computer interaction, accessible technology, and the use of technology in healthcare to improve patient experience. He is currently working to engage healthcare providers and community members through an innovative online ‘Tweet Chat’! Additionally, he is contributing to the first empirical characterization of social media use in dementia research, which seeks to assess the benefits and harms of social media usage for research participation. In his spare time, you can find Grayden exploring Vancouver and playing simulation games.

Policy’s Role in the Use of Social Robots in Care Homes

Can policy help social robots provide ethical, dignified, and beneficial care for older adults? This question has been the subject of ongoing ethical debate concerning the use of social robots in care homes.

Around the world, the expanding population of older adults is increasing the need for care resources, straining health and aged care providers (1). The COVID-19 pandemic has further highlighted the negative consequences of overpacked and understaffed healthcare institutions (2). As governments seek solutions to reduce pressure on care homes, the use of social robots as a potential tool has been suggested.

Already, social robots have been studied in the context of older adult care to provide companionship, exercise, cognitive therapy and help with daily tasks (3). Although these studies have shown predominantly positive effects, the majority have assessed social robots in short-term situations, have had small sample sizes, or lack diversity and may not be generalizable to all cultures (3).

Studies from North America with larger sample sizes and longer time periods are showing variable results, with some older adults experiencing declines in loneliness and increased interaction with other older adults (4). Populations of care home residents with dementia also show variation in responses, suggesting that one approach to delivering care with social robots does not fit all (5). However, it is important to note that the social robot used in both of these studies is the same model that has been in use since 2003 (6). The field of social robotics is rapidly expanding, with many new types and models of robots released with a greater focus on end-users in their development (7,8). Research with such models done in care home contexts with generalizable samples is limited (3). Although more research is needed, social robots developed with users are showing promising preliminary results and could be a viable future solution to promoting well-being in the elderly (9).

To this end, social robots are showing great promise as beneficial tools in care homes. They can assist caregivers in situations where they are tired, distracted, overwhelmed, or not feeling very well (5). Social robots can be used to empower older adults to be more independent and to aid aging at-home care (2).

However, key ethical challenges in the use of social robot care assistants include autonomy, privacy, dignity, and bias (2). Autonomy can be suppressed or overridden by a social robot if, for example, a user is prevented from climbing on a chair to reach something in an effort to prevent a fall. Although the user’s safety is maintained, their autonomy and dignity may be diminished by the robot. Furthermore, the social robot’s monitoring features and social interaction with the user require data storage and use, which could interfere with the user’s privacy.

Currently, legislation around privacy and consumer protection could form the basis of government-enforced policies around social robots. However, in AI, self-regulation through developers has typically been the norm (2). Criticism to this point can be made in that self-regulation does not sufficiently protect the rights and safety of vulnerable populations such as older adults, and that manufacturers primarily protect their own interests.

This is where Johnston suggests ethics by design can ensure that ethical values of dignity, respect for autonomy and benevolence can be programmed into the robot’s behavior such that it protects the interests of the elderly. Johnston continues that to determine the “moral code” programmed into social robots and to monitor the ethical use of such systems within care home contexts, the use of clinical ethics committees can be employed. Ethics committees can provide consultation services, help in creating care home policies and procedures regarding social robots, and aid to resolve emerging ethical dilemmas. To counteract ethical biases in design, it is important that ethics committees consider multi-stakeholder perspectives. Emphasizing the voices of end-users tailors social robot functionality to the populations it will serve, and aids in user acceptance of social robots (10).

Furthermore, policies must consider both the benefits and drawbacks of using social in care home contexts (1). Potential benefits could include increased efficiency, increased welfare, physiological and psychological benefits, and increased satisfaction (1). There are, however, interesting objections to the use of social robots including the possibility that relations with robots can potentially displace human contact, that these relations could be harmful, that robot care is undignified and disrespectful, and that social robots are deceptive (1). These are ethical considerations that must be carefully balanced in a holistic policy aimed to maximize benefits for end-users while mitigating potential downsides to social robot use.

Although we are not yet at the stage where social robots can be used in a large-scale fashion across care homes in North America, it is important to anticipate their future ethical ramifications. By discussing policy-regulated ethical considerations, we are taking strides towards the responsible development and use of social robots with the goal of minimizing their potential for harm and ensuring their benefits for human care.

Bio: Anna Riminchan was born in Bulgaria, where she spent her early childhood before immigrating to Canada with her family. Anna is currently working towards a Bachelor of Science Degree, majoring in Behavioural Neuroscience and minoring in Visual Arts at the University of British Columbia. In the meantime, she is contributing to advancing research in neuroscience, after which, she plans to pursue a degree in medicine. In her spare time, you can find Anna working on her latest art piece! 

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References

1. Sætra HS. The foundations of a policy for the use of social robots in care. Technol Soc. 2020 Nov 1;63:101383.
2. Johnston C. Ethical Design and Use of Robotic Care of the Elderly. J Bioethical Inq. 2022 Mar 1;19(1):11–4.
3. Thunberg S, Ziemke T. Social Robots in Care Homes for Older Adults. In: Li H, Ge SS, Wu Y, Wykowska A, He H, Liu X, et al., editors. Social Robotics. Cham: Springer International Publishing; 2021. p. 475–86. (Lecture Notes in Computer Science).
4. Robinson H, MacDonald B, Kerse N, Broadbent E. The Psychosocial Effects of a Companion Robot: A Randomized Controlled Trial. J Am Med Dir Assoc. 2013 Sep 1;14(9):661–7.
5. Moyle W, Jones C, Murfield J, Thalib L, Beattie E, Shum D, et al. Using a therapeutic companion robot for dementia symptoms in long-term care: reflections from a cluster-RCT. Aging Ment Health. 2019 Mar 4;23(3):329–36.
6. PARO Therapeutic Robot [Internet]. [cited 2022 Jul 22]. Available from: http://www.parorobots.com/
7. Breazeal CL, Ostrowski AK, Singh N, Park HW. Designing Social Robots for Older Adults. 2019;10.
8. Östlund B, Olander E, Jonsson O, Frennert S. STS-inspired design to meet the challenges of modern aging. Welfare technology as a tool to promote user-driven innovations or another way to keep older users hostage? Technol Forecast Soc Change. 2015 Apr 1;93:82–90.
9. Hutson S, Lim SL, Bentley PJ, Bianchi-Berthouze N, Bowling A. Investigating the Suitability of Social Robots for the Wellbeing of the Elderly. In: D’Mello S, Graesser A, Schuller B, Martin JC, editors. Affective Computing and Intelligent Interaction. Berlin, Heidelberg: Springer; 2011. p. 578–87. (Lecture Notes in Computer Science).
10. Hameed I, Tan ZH, Thomsen N, Duan X. User Acceptance of Social Robots. In 2016.

Stigma around technology use by older adults

Canadians are living longer, healthier lives, resulting in a rapidly growing population of older adults. It is projected that the number of adults aged 65 and over in Canada will grow by 68% over the next two decades (1). One way to support the quality of life of this growing demographic is through technology. Assistive technologies (AT) such as blood pressure monitors (2), wheelchairs (3), and fall detectors (4) can promote the physical health of older adults. Social robots, AT that can interact with users (Figure 1), can assist older adults by improving mood (5), decreasing blood pressure (6), and reducing the need for analgesic and behavioural medication (7). Everyday information and communication technologies (EICT) – including mobile phones, computers, and email services – allow for regular communication with social contacts (3) and the ability to look up health information (8). Telemedicine provides a unique healthcare solution for older adults who face barriers to in-person care such as isolation, severe illness, and functional challenges (9).

Figure 1 – Social robots such as MiRo-E can interact with users. Adapted from MiRo-E University Research

Despite the known benefits of these technologies, there is a wide range of barriers to technology adoption by older adults. Such barriers include privacy concerns (10), inappropriate device design (11), and a lack of familiarity with technology (12). Another barrier is stigma around the use of technologies by older adults (5,10,13). Negative stereotypes of old age include increased dependency, disability, and disconnection from society (13,14). Furthermore, within technology research, ageing is often regarded as a ‘problem’ that technology may address (15). In this piece, I will summarize the literature on stigma around technology use by older adults and how we might address this issue.

Older adults often associate AT with negative stereotypes about ageing. For example, some older adults have stated that they are not ‘disabled’ or ‘old’ enough to require AT (16). In one research study, older adults who stated that they did not need AT recommended these devices for people who experience isolation, dependency, and disability (17). Some older adults feel that adopting AT signifies a loss of independence (4), and others experience feelings of embarrassment and incompetency when using AT (12). Furthermore, some older adults have expressed preference for items that are not necessarily ‘assistive’ or ‘medical’ in nature, such as an umbrella in place of a walking stick (2), a smartwatch with assistive features (4), or a shopping cart in place of a walker (16). On the other hand, EICT such as smartphones and computers are often regarded by older adults as a way to keep up with society, and thus older adults associate non-use of these technologies with negative ageing stereotypes (13). However, when learning to use EICT, many older adults experience embarrassment, anxiety, or fear of making mistakes (2,18). Some have reported feeling ‘older’ after encountering vision and haptic-related challenges while using EICT (13). Altogether, the literature shows that technologies often remind older adults of negative aspects of ageing. As a result, older adults are less likely to adopt these technologies.

Non-use of the technologies described above raises several issues, including a key neuroethical problem: decreased access to mental health benefits. For example, several online services that can improve mental health – such as telemedicine and tele-counselling services – are accessed through technologies such as smartphones and computers. Research has shown that interacting with social robot technologies can improve mood (5), and technologies such as smartphones allow people to stay in touch with one another (3), especially during the current COVID-19 pandemic where in-person contact is restricted. These are just a few mental health benefits that older adults who limit their use of technologies have reduced access to. As a result, there is a need to address key barriers to technology adoption, such as stigma.

One of the most important things we can do to address issues of stigma and non-use is to engage end-users in the process of device development. Older adults are often not consulted when technologies are being developed for them, leading to devices that are often misaligned with their needs and priorities (19). A study by Federici et al. found that the most common reason for device abandonment was an inappropriate device design (11). Incorporating ideas and feedback from older adults about device design, features, applications, affective considerations, and ethical concerns into the creation and implementation of technologies will likely result in devices that this population is more comfortable using.

Bio: Jaya Kailley is an Undergraduate Research Assistant under the supervision of Dr. Julie Robillard in the NEST Lab, and she is pursuing an Integrated Sciences degree in Behavioural Neuroscience and Physiology at the University of British Columbia. She currently supports research projects that aim to include end-users in the process of social robot development. Outside of work, Jaya enjoys playing the piano, reading, and spending time with her family and friends.

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References

1. Infographic: Canada’s seniors population outlook: Uncharted territory | CIHI [Internet]. [cited 2022 Jun 16]. Available from: https://www.cihi.ca/en/infographic-canadas-seniors-population-outlook-uncharted-territory
2. Chen K. Why do older people love and hate assistive technology? ‒ an emotional experience perspective. Ergonomics. 2020 Dec 1;63(12):1463–74.
3. Tomšič M, Domajnko B, Zajc M. The use of assistive technologies after stroke is debunking the myths about the elderly. Topics in Stroke Rehabilitation. 2018 Jan 2;25(1):28–36.
4. Caldeira C, Nurain N, Connelly K. “I hope I never need one”: Unpacking Stigma in Aging in Place Technology. In: CHI Conference on Human Factors in Computing Systems [Internet]. New Orleans LA USA: ACM; 2022 [cited 2022 Jun 10]. p. 1–12. Available from: https://dl.acm.org/doi/10.1145/3491102.3517586
5. Hung L, Liu C, Woldum E, Au-Yeung A, Berndt A, Wallsworth C, et al. The benefits of and barriers to using a social robot PARO in care settings: a scoping review. BMC Geriatr. 2019 Aug 23;19(1):232.
6. Robinson H, MacDonald B, Broadbent E. Physiological effects of a companion robot on blood pressure of older people in residential care facility: A pilot study. Australasian Journal on Ageing. 2015;34(1):27–32.
7. Petersen S, Houston S, Qin H, Tague C, Studley J. The Utilization of Robotic Pets in Dementia Care. Journal of Alzheimer’s Disease. 2017 Jan 1;55(2):569–74.
8. Vroman KG, Arthanat S, Lysack C. “Who over 65 is online?” Older adults’ dispositions toward information communication technology. Computers in Human Behavior. 2015 Feb 1;43:156–66.
9. Frydman JL, Li W, Gelfman LP, Liu B. Telemedicine Uptake Among Older Adults During the COVID-19 Pandemic. Ann Intern Med. 2022 Jan;175(1):145–8.
10. Pirzada P, Wilde A, Doherty GH, Harris-Birtill D. Ethics and acceptance of smart homes for older adults. Informatics for Health and Social Care. 2021 Jul 9;1–28.
11. Federici S, Meloni F, Borsci S. The abandonment of assistive technology in Italy: A survey of users of the National Health Service. European journal of physical and rehabilitation medicine. 2016;52(4):516–26.
12. Evans N, Boyd H, Harris N, Noonan K, Ingram T, Jarvis A, et al. The experience of using prompting technology from the perspective of people with Dementia and their primary carers. Aging & Mental Health. 2021 Aug 3;25(8):1433–41.
13. Köttl H, Gallistl V, Rohner R, Ayalon L. “But at the age of 85? Forget it!”: Internalized ageism, a barrier to technology use. Journal of Aging Studies. 2021 Dec 1;59:100971.
14. Dionigi RA. Stereotypes of Aging: Their Effects on the Health of Older Adults. Journal of Geriatrics. 2015 Nov 12;2015:1–9.
15. Vines J, Pritchard G, Wright P, Olivier P, Brittain K. An Age-Old Problem: Examining the Discourses of Ageing in HCI and Strategies for Future Research. ACM Trans Comput-Hum Interact. 2015 Mar 4;22(1):1–27.
16. Astell AJ, McGrath C, Dove E. ‘That’s for old so and so’s!’: does identity influence older adults’ technology adoption decisions? Ageing and Society. 2020 Jul;40(7):1550–76.
17. Wu YH, Wrobel J, Cornuet M, Kerhervé H, Damnée S, Rigaud AS. Acceptance of an assistive robot in older adults: a mixed-method study of human–robot interaction over a 1-month period in the Living Lab setting. Clin Interv Aging. 2014 May 8;9:801–11.
18. University of Massachusetts Lowell, McDonough CC. The Effect of Ageism on the Digital Divide Among Older Adults. GGM. 2016 Jun 16;2(1):1–7.
19. Mannheim I, Schwartz E, Xi W, Buttigieg SC, McDonnell-Naughton M, Wouters EJM, et al. Inclusion of Older Adults in the Research and Design of Digital Technology. Int J Environ Res Public Health. 2019 Oct;16(19):3718.

The significance of non-pharmacological treatments for depression in people living with dementia

As part of my role in the Neuroscience, Engagement, and Smart Tech (NEST) Lab at Neuroethics Canada, I conducted a review of non-pharmacological interventions for mental health in people living with dementia. What are these non-pharmacological interventions, and why are researchers so interested in studying them?

Among the 50 million people worldwide with a diagnosis of dementia, roughly 32% (16 million) report symptoms of depression (1). Within this group, half will have received a formal diagnosis of major depressive disorder. You may already be familiar with pharmacological or drug-based interventions for depression (e.g., antidepressants). However, in recent years, there has been a push for non-pharmacological treatment alternatives for people living with dementia.

Non-pharmacological treatments are defined as any activity or care plan to reduce symptoms of a given ailment. These interventions are often adjustable to accommodate the needs of the recipients, something traditional drug interventions lack.

The issues surrounding pharmacological treatments for depression

Various studies highlight some of the drawbacks surrounding the drug interventions commonly used to treat major depressive disorder. The findings of a 2013 study revealed that 69% of older adults from a data sample of 2 million received a prescription psychotropic without a formal psychiatric diagnosis (2). In addition, many were found to not be receiving any type of mental health specialty care (2).

Figure 1 – Weichers et. al (2013). Percentage of mental health care utilizers and non–mental health care utilizers without a psychiatric diagnosis who filled a prescription for psychotropic medication in 2009, by age and drug class. AD, antidepressants; AP, antipsychotics; ANX, anxiolytics; STIM, stimulants; MS/AC, anticonvulsant mood stabilizers; and LITH, lithium.

These results come with caveats. Not being able to qualify for a diagnosis does not negate the existence of a medical need, nor does it address the social barriers individuals may face in obtaining a diagnosis. Experiencing symptoms can drastically impact a person’s physical health and overall quality of life (3). Symptoms are expressed in a multitude of ways (e.g., lethargy, insomnia, changes in appetite, feeling discouraged or unhappy) and in varying intensities (4). Depression manifests itself differently for each individual and depending on their given situation, clinical treatment may have been the best course of action.

Nevertheless, the study results suggest that the current implementation of clinical approaches to treating depression may not meet the desired standards of care (2). Also consider the high relapse rates of major depressive disorder in individuals exclusively using pharmacological therapies (5).

The efficacy of drug interventions for treating depression in people living with dementia has been challenged by various studies (6,7,8). Evidence indicates that antidepressants are associated with an increased risk of recurrent falls, whereas non-pharmacological care alternatives have the potential to be just as effective as drug treatments with fewer risks (6,7).

Certain psychological treatments can match the effectiveness of clinical approaches to mood disorders (4), and a few are somewhat more effective (6). Drug interventions alone can be an effective treatment method for many (5,6,7). However, we must also assess the ethical considerations surrounding limited catalogues of treatment options only optimal for a subset of individuals.

Thus, there is unexplored potential in the application of non-pharmacological interventions as both a supplement to drug treatments and as their own form of care.

Sociocultural and ethical considerations

The myriad of issues related to treatments for mental health in people living with dementia are complex. A discussion regarding healthcare disparities and the socioeconomic and cultural barriers to care could warrant a post of its own. Here, I will attempt to summarize a few.

• Stigma — There may be cultural stigma surrounding mental health and treatment (8,9). Individuals who inherit cultural values from their respective culture or community may not feel comfortable with western conventions of mental health. Thus, given how drug interventions are prescribed in Canada, pharmacological treatments may not be the most effective or accessible option.
• Economic factors — Prescription drug costs contribute to the inaccessibility of treatment. Canada is the only developed country with a universal healthcare system that does not cover the cost of prescription drugs. Older adults without private health insurance may be left in a difficult position (10).
• Location — Individuals living in rural or remote locations may face difficulty with filling their prescriptions over an extended period (11).

There are many more issues pertaining to the limitations of drug interventions in current healthcare models. Thus, there is value in exploring non-pharmacological treatment alternatives (6).

How non-pharmacological interventions for depression can be used

In recent years, there has been growing interest in social prescribing: the act of linking patients with non-drug interventions in their community (6). While non-profit organizations such as the Alzheimer’s Society of BC are unable to prescribe medication, they can provide low or no-cost services aiming to support mental health.

Implementing these non-pharmacological interventions can also be a quite simple. Some common, low-cost interventions that are easy to implement include:

• Reminiscence therapy — Remembering or sharing details about the past or previous positive events, either alone or with a group. Reminiscence therapy can improve quality of life, cognitive functions, and lower depression (12).
• Exercise — Exercising the body and the mind can reduce symptoms of depression and improve the overall quality of life (6).
• Music therapy — Listening to music regularly with a music therapist can improve symptoms of depression (13).
• Indoor Daylight Exposure —People living with dementia at a nursing home socialized with each other in an indoor setting with ample amounts of daylight each morning. Daylight exposure was found to significantly reduce symptoms of depression (14).

These interventions do not present as very psychological or medical in nature. By framing activities that may reduce symptoms of depression in an approachable, non-clinical manner, care providers could avoid the stigmas around treatment for mental health to encourage greater use of mental health services (15). However, this does not address the issues surrounding mental health perception and discourse. More research is needed to better understand how we can effectively tackle these stigmas.

Providing evidence-based, low-complexity care can also enable people living with dementia to form deeper bonds with their local community and create their own support network. The low cost of execution makes these interventions a great option for treating mild symptoms of depression.

Complex interventions that target more severe symptoms of depression and aim to create lasting effects also exist. These require a higher degree of training from providers and thus are more costly, but evidence highlights their value as potential treatment options (6, 16, 17, 18). Examples include:

• Cognitive-behavioral therapy (CBT) — Breaking down existing negative cognitions and replacing them with more positive functionally adaptive ones (16) can reduce symptoms of both depression and anxiety (6, 17, 18).
• Multidisciplinary care — A care plan developed in collaboration with multiple qualified healthcare providers can match the efficacy of drug treatments (6).

There are many other approaches: animal-assisted activities, psychotherapy, cognitive stimulation, and environmental modification, to name a few (6). Non-pharmacological interventions also have the advantage of being flexible and adjustable to one’s individual needs. For example, Shiatsu could be an interesting approach for people with dementia of East Asian descent.

• Shiatsu — A holistic complementary practice that draws on the principles of traditional Chinese medicine. By applying pressure to certain pressure points, symptoms of depression were reduced when utilized in combination with exercise (19).

Figure 2 – a man performs Shiatsu therapy (left) with a focus on key acupressure points (right).
Credit: Shiatsu Tokyo School, 2021.

Many treatment options exist where traditional drug-based interventions are not appropriate. Individuals could develop a personalized care plan with careful guidance from a qualified medical professional.

There is still an important need for drug interventions. For a subset of the population, it remains quite effective (5,6).

The value in exploring various non-pharmacological treatments has much to do with the agency it gives the individual and how it makes mental health care more attainable to people of all socioeconomic and cultural backgrounds.

Looking to the future

Non-pharmacological interventions may reduce the burden of depressive symptoms in older adults with dementia. Within the next few decades, the global population will continue to age and the number of people living with dementia is expected to increase to 152.8 million cases by 2050 (20). Thus, the need for programs supporting the well-being of older (and younger!) adults with dementia is greater than ever.

In neuroethics research, the way non-pharmacological interventions are received and their overall effectiveness can be studied to highlight healthcare disparities and bring insight into public discussions surrounding brain health and aging. This research may inform initiatives that aim to address the gap in services related to mental health in people living with dementia.

By deepening our understanding of how people living with dementia respond to non-pharmacological interventions, we can improve current treatment approaches and the standard of care. Every individual should have the option to receive the type of care that best suits their specific medical needs.

Special thanks to Dr. Julie Robillard and Viorica Hrincu from the NEST Lab for all their guidance and support in the last year!

Bio: Yu Fei Jiang is a 4^th-year undergraduate student studying Behavioural Neuroscience at the University of British Columbia. Her research interests primarily lie in the interaction between technology use in patient care and neuroscience research. She’s also very passionate about science communication and sharing knowledge with others. Outside of work, Yu Fei enjoys all things nerdy; you’ll probably find her either reading books of wildly different genres or playing video games late into the night.

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References

1. Goodarzi ZS, Mele BS, Roberts DJ, Holroyd-Leduc J. (2017). Depression Case Finding in Individuals with Dementia: A Systematic Review and Meta-Analysis. J Am Geriatric Society, 65, 937-48. Doi.org/10.1111/jgs.14713

2. Wiechers, I. R., Leslie, D. L., Rosenheck, R. A. (2013). Prescribing of psychotropic medications to patients without a psychiatric diagnosis. Psychiatric Services, 64(12), 1243–1248. https://doi.org/10.1176/appi.ps.201200557

3. Ruo, B., Rumsfeld, J. S., Hlatky, M. A., Liu, H., Browner, W. S., & Whooley, M. A. (2003). Depressive symptoms and health-related quality of life: the Heart and Soul Study. Jama, 290(2), 215-221.

4. Spitzer, R. L., Kroenke, K., Williams, J. B., Patient Health Questionnaire Primary Care Study Group, & Patient Health Questionnaire Primary Care Study Group. (1999). Validation and utility of a self-report version of PRIME-MD: the PHQ primary care study. Jama, 282(18), 1737-1744.

5. Beck, A. T., & Alford, B. A. (2009). Depression: Causes and treatment. University of Pennsylvania Press.

6. Watt J A, Goodarzi Z, Veroniki A A, Nincic V, Khan P A, Ghassemi M et al. (2021). Comparative efficacy of interventions for reducing symptoms of depression in people with dementia: systematic review and network meta-analysis BMJ; 372 :n532 doi:10.1136/bmj.n532

7. Marcum, Z. A., Perera, S., Thorpe, J. M., Switzer, G. E., Castle, N. G., Strotmeyer, E. S., Simonsick, E. M., Ayonayon, H. N., Phillips, C. L., Rubin, S., Zucker-Levin, A. R., Bauer, D. C., Shorr, R. I., Kang, Y., Gray, S. L., Hanlon, J. T., & Health ABC Study (2016). Antidepressant Use and Recurrent Falls in Community-Dwelling Older Adults: Findings From the Health ABC Study. The Annals of pharmacotherapy, 50(7), 525–533. https://doi.org/10.1177/1060028016644466

8. Ng, C. H. (1997). The stigma of mental illness in Asian cultures. Australian & New Zealand Journal of Psychiatry, 31(3), 382-390.

9. Ciftci, A., Jones, N., & Corrigan, P. W. (2013). Mental health stigma in the Muslim community. Journal of Muslim Mental Health, 7(1).

10. Morgan, S. G., & Boothe, K. (2016). Universal prescription drug coverage in Canada: Long-promised yet undelivered. Healthcare management forum, 29(6), 247–254. https://doi.org/10.1177/0840470416658907

11. Hippe, J., Maddalena, V., Heath, S., Jesso, B., McCahon, M., & Olson, K. (2014). Access to health services in Western Newfoundland, Canada: Issues, barriers and recommendations emerging from a community-engaged research project. Gateways: International Journal of Community Research and Engagement, 7(1), 67-84.

12. Lök, N., Bademli, K., & Selçuk‐Tosun, A. (2019). The effect of reminiscence therapy on cognitive functions, depression, and quality of life in Alzheimer patients: Randomized controlled trial. International journal of geriatric psychiatry, 34(1), 47-53.

13. Li, H. C., Wang, H. H., Lu, C. Y., Chen, T. B., Lin, Y. H., & Lee, I. (2019). The effect of music therapy on reducing depression in people with dementia: A systematic review and meta-analysis. Geriatric Nursing, 40(5), 510-516.

14. Konis, K., Mack, W. J., & Schneider, E. L. (2018). Pilot study to examine the effects of indoor daylight exposure on depression and other neuropsychiatric symptoms in people living with dementia in long-term care communities. Clinical interventions in aging, 13, 1071.

15. Corrigan, P. (2004). How stigma interferes with mental health care. American psychologist, 59(7), 614.

16. Taylor, F. G., & Marshall, W. L. (1977). Experimental analysis of a cognitive-behavioral therapy for depression. Cognitive Therapy and Research, 1(1), 59-72.

17. García-Alberca, J. M. (2017). Cognitive-behavioral treatment for depressed patients with Alzheimer’s disease. An open trial. Archives of gerontology and geriatrics, 71, 1-8.

18. Tay, K. W., Subramaniam, P., & Oei, T. P. (2019). Cognitive behavioural therapy can be effective in treating anxiety and depression in persons with dementia: a systematic review. Psychogeriatrics, 19(3), 264-275.

19. Lanza, G., Centonze, S. S., Destro, G., Vella, V., Bellomo, M., Pennisi, M., … & Ciavardelli, D. (2018). Shiatsu as an adjuvant therapy for depression in patients with Alzheimer’s disease: A pilot study. Complementary therapies in medicine, 38, 74-78.

20. Nichols, Emma, et al. (2022). Estimation of the Global Prevalence of Dementia in 2019 and Forecasted Prevalence in 2050: An Analysis for the Global Burden of Disease Study 2019. The Lancet Public Health. 7(2):105–25.

Experimental Neuroethics

Photo credit: Timothy Epp, Shutterstock

Four years ago, Neil Levy gave the concluding lecture at the first Brain Matters conference in Halifax. He alerted the audience of neuroethicists to the fact that the field of philosophy was undergoing a revolution – rather than muse from their armchairs in the ivory tower, a group of renegade philosophers were carrying out real experiments, asking people what their intuitions were about central issues in philosophy. Dubbed experimental philosophy, the new initiative was met with more than passing resistance from traditional philosophers. The apostate experimental philosophers responded by developing a logo of a burning armchair.

The landmark experiment was carried out by Josh Knobe, and its findings subsequently became known as the Knobe effect (you can watch a great recreation of the phenomenon in this YouTube video). Essentially, what Josh did was repurpose an old method from social psychology called the contrastive vignette technique (CVT) [1]. At its simplest, the CVT involves designing a pair of vignettes that carefully describe a particular situation (in the case of experimental philosophy, one that is often morally charged) but crucially differ in one detail, hence the term contrastive. Respondents see one and only one version of the vignette, and are then asked questions about what they have just read, with responses commonly recorded as a numerical rating on a Likert scale. By comparing the averaged responses between separate groups of people who have read the vignettes, the experimenter can systematically investigate the effects of small changes (of which the respondents are entirely unaware) upon attitudes towards nearly any topic. The experimental philosophers tend to use the technique to explore the meaning of concepts. Neil Levy pointed out that this same approach could, in principle, be applied to the full range of issues in neuroethics.

Neil’s presentation struck me like a thunderbolt. I had come to the field of neuroethics with a background in cellular and molecular biology, and had spent much of my career as a card-carrying reductionist: as a graduate student in the 1980’s, I championing the then-novel technique of recording from single neurons in freely moving animals, and as a postdoc I moved on to the better controlled (if less naturalistic) technique of patch clamp analysis of identified neurons in slices of brains. My subsequent rise through the ranks of academia was one in which I applied quantitative rigor to every question that I asked, and in the circles in which I traveled, this was lauded as the ultimate way to provide reproducible (and by inference, meaningful) results. I saw at once that the CVT opened the door towards doing something similar in the field of neuroethics.

My research group at the National Core for Neuroethics has embraced the use of contrastive vignettes wholeheartedly, and with a nod to the experimental philosophy camp, we call the approach Experimental Neuroethics. The team is applying the technique to a range of issues in contemporary neuroethics, probably best exemplified by our recent publications exploring public attitudes towards cognitive enhancement [2] as well as the acceptability of overt and covert nudges [3].

If the vignettes appear simple, I can assure you that properly crafting them is hard work. We begin with a carefully considered hypothesis and regularly find that the hypothesis morphs substantially (usually into something much more insightful) as the process unfolds. We then compose two or more contrastive vignettes, working hard to have the vignettes as minimally contrastive as possible (one word differences between vignettes is the ultimate goal, but this is often not feasible). Finally, we develop questions; we like to have the wording of the questions always be identical irrespective of the contrastive nature of the vignette.

Then the real fun begins. After a day or two, we assemble as a team and attack our previous work. Inevitably, we find it wanting in some respect. Sometimes, embarrassingly so. We find it best to begin by asking whether the vignette and the questions directly address the hypothesis. Sometimes that means that the hypothesis changes. Nearly always, that means that the vignette changes. This process is repeated again and again, over days and weeks and sometimes months (yes, and even sometimes years!) until we have a set of vignettes that get to the heart of the matter.

At some point late in the process we carry out cognitive pre-testing. This involves sharing the vignette and the questions with someone who has no particular expert knowledge (friends of friends are likely culprits), and debriefing them about what they read. We are sometimes amazed to find that what we intended for people to glean from a vignette is at odds with their reading of the vignette. That sends us back to the drawing board.

We also run some metrics to determine whether the words we have used are understandable by a general audience. We use online readability tests such as this one to establish the educational level required for understanding the vignette; our goal is that no more than a high school education is required. Finally, we launch the survey, recruiting respondents from amongst the thousands of people who have signed up on Amazon’s Mechanical Turk – they’re more representative of the real population and aren’t as blatantly WEIRD as typical undergraduate samples. And then we hold our breath.

Once the data is analyzed, we get mired once again in deep discussion. For it is not just the quantitative aspect of Experimental Neuroethics that it satisfying (to me), but also that the data gives us an entirely new benchmark for engaging in the process of wide reflective equilibrium. Throughout this process we remain aware that an ought can not derive from is, but having the data at hand, our version of ought is very much informed by the is. Ultimately, our data emerge in concert with our normative insights, and then one more advantage of Experimental Neuroethics is realized: it is easy for others to replicate our experiments, or even to improve them by taking our vignettes and modifying them to further test their own. This iterative process of replication, critique, and systematic modification has proven to be a robust strategy for advancing insights into the nature of biological and physical phenomena. Only time will tell whether Experimental Neuroethics catches fire in our discipline as it has in the field of philosophy (where it remains controversial). If it does, we can trace it back to Neil’s presentation in Halifax….

[Cross posted at the Neuroethics Blog]

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[1] Burstin K, Doughtie E, Raphaeli A. Contrastive Vignette Technique: An indirect Methodology Designed to Address Reactive Social Attitude Measurement1. Journal of Applied Social Psychology. 1980;10(2):147–65.

[2] Fitz NS, Nadler R, Manogaran P, Chong EWJ, Reiner PB. Public attitudes toward cognitive enhancement. Neuroethics. 2013 doi: 10.1007/s12152-013-9190-z.

[3] Felsen G, Castelo N, Reiner PB. Decisional enhancement and autonomy: public attitudes towards overt and covert nudges. Judgment and Decision Making. 2013;8(3):202–13.

Graphic Warnings on Cigarettes: Nudge or Shove? A Neuro-Perspective

Although the topic of cigarette packaging regulation may not leap immediately to mind when one thinks “neuroethics,” this Bob Greene opinion piece over at CNN nonetheless touched off a stimulating discussion among some of us at the Core recently. The neuroethics connection, in fact, struck us as quite natural: our group has researched (and blogged about) the ethics of “nudging” frequently of late, and, as I worded it when I first emailed the article around, “certainly the images at issue here are a kind of behavioural nudge.” The question that we grappled with was whether the kind of nudge that the graphic warning labels provide is warranted in the case of cigarettes. And, indeed, that discussion called my original characterization into question. Do these labels truly constitute a nudge – a subtle biasing technique that makes a particular option more cognitively accessible than another while preserving the freedom to choose between them – or are they something more akin to a “shove?”

One of the least gruesome of the proposed images for cigarette packs.

As with any highly politicized issue, the question of whether cigarettes ought to be labeled with disturbing imagery is likely to be filleted into oblivion by pundits, bloggers, legal experts, economists, et cetera, et cetera. All I hope to do here, then, is sketch some ways in which the view from neuroethics – informed as it is by philosophy and the cognitive sciences – can shed some interesting and hopefully useful light on the question.

TDCS does not reduce the authenticity objection

In an essay in recent issue of Current Biology, a team of neuroscientists and philosophers examine the neuroethics of transcranial direct current stimulation (TDCS), a relatively inexpensive means of modifying human brain activity that is touted as potentially being at the forefront of a new wave of cognitive enhancement. The article has garnered a great deal of interest in the press (for example here and here and here), and the reasons are unsurprising: the prospect of a device that is cheap (probably), safe (maybe), and effective (time will tell) is something akin to the holy grail of cognitive enhancement. If the initial claims for TDCS hold up, the device may have an impact the practice of enhancement in the relatively near term. As a result, the urgency with which our community must think through the relevant ethical issues intensifies.

The trolley problem and the evolution of war

The trolley problem is a famous thought experiment in philosophy, and runs something like this.

A runaway trolley is hurtling down a track. Five people have been tied to the track directly in front of the trolley, but there is a switch which allows the trolley to be diverted to an alternative track where one person has been tied to the track. You are standing at the switch and see the disaster unfolding. What do you do?  Most people answer that they would flip switch, killing one to save five – classic utilitarian thinking. The trolley problem has been embellished in a variety of interesting ways. The most famous of these is called the fat man problem: 5 people are tied to the track as before, but now there is a fat man on a bridge over the track, and if you push him off, he will fall before the train, stopping it and saving 5 people as before; of course, the fat man dies in the process. People who were willing to pull the switch to save 5 people tend to be reluctant to push the fat man off the bridge. Philosophers suggest that this reluctance is based upon deontological thinking, where one’s deep-seated values determine one’s actions rather than cool rational thought.

Neuroethics Journal Club: Judging Mens Rea

The National Core for Neuroethics had a lively journal club discussion recently on a paper by Bertram Malle and Sarah Nelson that dealt with “the tension between folk concepts and legal concepts of intentionality.” As I was presenting the paper and facilitating the discussion, I decided to blog about it to share some of the highlights with our readers and crystallize my own thoughts on the matter, stirred up as they were by the proceedings.

The basic gist of the paper is as follows. Malle and Nelson identify “the valid and precise use of the concepts of mental states in reasoning about the defendant’s actions and in assigning responsibility, blame, and punishment” as a central challenge in creating a system of criminal adjudication. (One interesting point to consider going forward is how these same issues might apply to the context of torts, where instead of the epistemic criterion being “beyond a reasonable doubt” one is instead prompted to consider “the balance of evidence.”) In legal contexts, the term used to refer to the mental states in question is mens rea, Latin for “guilty/sinful mind.”

The specific mental state that the paper is concerned with is intention, especially as it relates to intentional action. In the grand tradition of experimental philosophy (though it really wasn’t yet a tradition in 2003!), Malle and Nelson find the by-now familiar faults with how these concepts have been developed in legal theory and philosophy – with theories of intentional action checked primarily against the intuitions of a small, non-representative group of participants in the debate, leading to a confusing mismatch between how the law asks us to use concepts, and how we (generally) are inclined to actually use them.

The paper explores the possibility of replacing the contorted and awkward legal concept of intentionality (here used as a synonym for intentional action) with a “folk” theory, one which Malle and a then-lesser-known Joshua Knobe had already undertaken to construct via several studies. Malle’s rationale is that, should the folk concept of intentionality prove to be consistent in its use and appropriate to the goals of law, it will be a natural successor to the status quo.