Text (Instruction Step Text)
From The Embassy of Good Science
Describe the actions the user should take to experience the material (including preparation and follow up if any). Write in an active way.
- ⧼SA Foundation Data Type⧽: Text
1
click and exercise the quiz. +
'''Questions to consider:'''
• Whose knowledge is treated as legitimate in this research?
• Are we prioritising certain forms of knowledge, experience, or expertise over others?
• Are we systematically undervaluing certain perspectives or experiences or treating them as less credible?
• Are the perspectives, values, or practices of affected groups acknowledged and respected?
• Are all contributions to the research process appropriately credited?
'''Example :''' A climate adaptation project relies exclusively on technical models developed by external experts, while local or experiential knowledge is not considered relevant to the research. Reflecting on epistemic and recognition justice highlights whether important insights are being overlooked and whether some perspectives are implicitly treated as less credible or valuable. +
[[File:AI img10.png|center|frameless|600x600px]]
Comité Consultatif National D’Ethique pour les Sciences de la Vie et de la Santé:
Medical Diagnosis and Artificial Intelligence: Ethical Issues. Joint opinion of the CCNE and CNPEN,
CCNE Opinion 141, CNPEN Opinion 4. November 2022
https://www.ccne-ethique.fr/sites/default/files/2023-05/Opinion%20No.141.pdf
Council of Europe:
Guidelines on artificial intelligence and data protection (2019)
https://ec.europa.eu/info/funding-tenders/opportunities/docs/2021- [https://ec.europa.eu/info/funding-tenders/opportunities/docs/2021-2027/horizon/guidance/ethics-by-design-and-ethics-of-use-approaches-for-artificial-intelligence_he_en.pdf 2027/horizon/guidance/ethics-by-design-and-ethics-of-use-approaches-] [https://ec.europa.eu/info/funding-tenders/opportunities/docs/2021-2027/horizon/guidance/ethics-by-design-and-ethics-of-use-approaches-for-artificial-intelligence_he_en.pdf for-artificial-intelligence_he_en.pdf]
Deutscher Ethikrat (German Ethics Council):
Opinion: Humans and Machines – Challenges of Artificial Intelligence (2023) https://www.ethikrat.org/en/publications/publication-details/?tx_wwt3shop_detail%5Bproduct%5D=168&tx_wwt3shop_detail%5Baction%5D=index&tx_wwt3shop_detail%5Bcontroller%5D=Products&cookieLevel=accept-all&cHash=4d430bf45ea980ea5f83daad9550ef88 (currently only available in German, an English translation will be available in due course)
European Commission:
Ethics By Design and Ethics of Use Approaches for Artificial Intelligence (2021)
https://ec.europa.eu/info/funding-tenders/opportunities/docs/2021- [https://ec.europa.eu/info/funding-tenders/opportunities/docs/2021-2027/horizon/guidance/ethics-by-design-and-ethics-of-use-approaches-for-artificial-intelligence_he_en.pdf 2027/horizon/guidance/ethics-by-design-and-ethics-of-use-approaches-] [https://ec.europa.eu/info/funding-tenders/opportunities/docs/2021-2027/horizon/guidance/ethics-by-design-and-ethics-of-use-approaches-for-artificial-intelligence_he_en.pdf for-artificial-intelligence_he_en.pdf]
European Commission Science Policy, Advice & Ethics Unit, DG Research & Innovation:
The ethics appraisal scheme in Horizon Europe (2021)
https://www.bbmri-eric.eu/wp-content/uploads/The-Ethics-Appraisal-Scheme-_BBMRI-webinar-september-2021_version-for-dessimination.pdf
Chapter 8 of the ethics issues table in the EU ethics appraisal scheme is of particular importance in Horizon Europe as it specifically addresses research ethical aspects of AI. Other relevant chapters include chapter 1 on human participants, chapter 4 on personal data and chapter 10 on the potential misuse of results. The inclusion of a chapter on AI in Horizon Europe is a recent addition. The EC introduced this chapter because it identified pressing ethical concerns related to discrimination and bias, safety and liability, transparency and opaque algorithms, as well as privacy and data protection. These concerns were deemed highly urgent and thus warranted a dedicated section within the ethics appraisal scheme. The key values to be respected within the projects submitted to the EU appraisal scheme are (1) human agency and oversight, (2) privacy and data protection, (3) fairness, diversity and non-discrimination, (4) accountability, (5) transparency, and (6) societal and environmental wellbeing.
Ethics guidelines for trustworthy AI (2019)
https://digital-strategy.ec.europa.eu/en/library/ethics-guidelines- [https://digital-strategy.ec.europa.eu/en/library/ethics-guidelines-trustworthy-ai trustworthy-ai]
OECD Legal Instruments:
Recommendation of the Council on Artificial Intelligence (2019)
https://legalinstruments.oecd.org/en/instruments/oecd-legal-0449
UNESCO:
Recommendations on the Ethics of Artificial Intelligence (2022)
https://unesdoc.unesco.org/ark:/48223/pf0000381137
World Health Organisation:
Ethics and governance of artificial intelligence for health (2021)
https://www.who.int/publications/i/item/9789240029200
See Chapter 4 for an overview of laws, policies, and principles that apply to the use of AI in healthcare. Chapter 5 proposes six key ethical principles which can serve as useful reminders for those involved in research utilising AI in healthcare
Also worth exploring are guidelines produced by [https://blog.neurips.cc/2021/12/03/a-retrospective-on-the-neurips-2021-ethics-review-process/ Stanford University], [https://unesdoc.unesco.org/ark:/48223/pf0000380455#:~:text=AI%20actors%20and%20Member%20States,law%2C%20in%20particular%20Member%20States%27 UNESCO] and the Horizon Europe Project [https://www.sienna-project.eu/ SIENNA] which developed ethical frameworks and recommendations for AI and robotics.
Isaak, J., & Hanna, M. J. (2018). User data privacy: Facebook, Cambridge Analytica, and privacy protection. Computer, 51(8), 56-59. https://ieeexplore.ieee.org/abstract/document/8436400
<div><div>
ALLEA (2023) The European Code of Conduct for Research Integrity, Revised edition, available from: [https://eneri.eu/the-project/ https://allea.org/]
World Medical Association, Declaration of Helsinki – Ethical Principles for Medical Research Involving Human Subjects, available from: https://www.wma.net/policies-post/wma-declaration-of-helsinki-ethical-principles-for-medical-research-involving-human-subjects/
ENERI (nd) National RE and RI infrastructure, available from: [https://www.bps.org.uk/guideline/bps-code-human-research-ethics https://eneri.eu/national-re-and-ri-infrastructure/]
The San Code of Research Ethics, available from: [https://www.hra.nhs.uk/about-us/committees-and-services/res-and-recs/ https://www.globalcodeofconduct.org/affiliated-codes/]
Singapore Statement, available from: [https://www.globalcodeofconduct.org/affiliated-codes/ https://www.wcrif.org/downloads/main-website/singapore-statements/223-singpore-statement-a4size/file]
The TRUST Global Code of Conduct for Equitable Research Partnerships, available from: [https://allea.org/ https://www.globalcodeofconduct.org/]
</div></div><div>
{| class="wikitable"
|[https://classroom.eneri.eu/node/218 Previous Page]
|[https://classroom.eneri.eu/node/131 Return to iRECS Learning Material]
|}
</div> +
<div><div>
In this module we have considered key concepts associated with the use of AI technologies in healthcare, including how AI systems are built, some of the key applications available for use in healthcare, and the primary implications of their use within the healthcare domain.
Now you can try the end of module quiz to see whether your learning from this module addresses the intended learning outcomes.
</div></div><div><div></div></div> +
In addition to the checklist that we have been referring to throughout this case study, we also recommend consulting the policies and guidelines below when reviewing proposals involving the use of XR technologies. There are currently no specific EU or international guidelines governing XR. Listed here are the most relevant sources of ethics guidance as well as the most relevant regulations.
A not-for-profit organisation, The '''Metaverse Standards Forum''' brings together most of the industrial players involved in the metaverse, with the aim of creating the conditions for its worldwide interoperability: [https://metaverse-standards.org/ https://metaverse-] [https://metaverse-standards.org/ standards.org/]
'''Data Privacy and Security'''
[https://gdpr-info.eu/ General Data Protection Regulation (GDPR)]
The GDPR is a comprehensive data protection law that applies to all research involving personal data from EU citizens, regardless of where the research is conducted.
'''Guidelines for AI and Emerging Technologies'''
[https://www.oecd.org/en/topics/policy-issues/artificial-intelligence.html OECD Principles on Artificial Intelligence]
These principles promote responsible stewardship of trustworthy AI, calling for transparency, accountability, and data privacy. For XR studies that integrate AI-driven avatars or generative AI, these guidelines emphasise transparency in AI functionality and accountability for AI-driven outcomes.
[https://www.unesco.org/en/articles/recommendation-ethics-artificial-intelligence UNESCO’s Recommendation on the Ethics of Artificial Intelligence] (2021)
UNESCO’s guidelines focus on AI ethics, covering respect for human rights, transparency, and accountability. This is particularly relevant to XR studies that use AI to create immersive experiences, as researchers must ensure that AI-driven interactions are fair, transparent, and respectful of human dignity.
[https://digital-strategy.ec.europa.eu/en/library/ethics-guidelines-trustworthy-ai European Commission’s Ethics Guidelines for Trustworthy AI]
These guidelines emphasise the need for AI systems to be lawful, ethical, and robust. In XR research involving AI avatars, this means ensuring that AI interactions do not mislead or psychologically manipulate participants and that data collected from these interactions complies with ethical standards.
Ethics By Design and Ethics of Use Approaches for Artificial Intelligence (2021)
https://ec.europa.eu/info/funding-tenders/opportunities/docs/2021- [https://ec.europa.eu/info/funding-tenders/opportunities/docs/2021-2027/horizon/guidance/ethics-by-design-and-ethics-of-use-approaches-for-artificial-intelligence_he_en.pdf 2027/horizon/guidance/ethics-by-design-and-ethics-of-use-approaches-] [https://ec.europa.eu/info/funding-tenders/opportunities/docs/2021-2027/horizon/guidance/ethics-by-design-and-ethics-of-use-approaches-for-artificial-intelligence_he_en.pdf for-artificial-intelligence_he_en.pdf]
Provides a comprehensive framework to ensure the ethical development and deployment of AI-driven avatars. E'''thics by Design''' guides the development of AI systems that prioritize privacy, transparency, and fairness from the outset. '''Ethics of Use e'''mphasizes ethical considerations during deployment, including informed consent, impact monitoring, participant support, and continuous feedback mechanisms.
[https://digital-strategy.ec.europa.eu/en/policies/european-approach-artificial-intelligence European approach to artificial intelligence]
Includes links to the current relevant guidelines, strategies and support that are relevant in the EU. Focusses on excellence and trust and aiming to boost research and industrial capacity while ensuring safety and fundamental rights.
World Health Organisation: Ethics and governance of artificial intelligence for health (2021)
https://www.who.int/publications/i/item/9789240029200
Although the WHO guidelines specifically address AI in health contexts, many principles are broadly applicable to XR research that uses AI and involves psychological and biometric assessments. The guidelines reinforce the importance of transparency, accountability, privacy, risk mitigation, fairness, and informed consent—all critical to conducting AI-driven research in immersive XR environments. While these guidelines are framed around health their principles apply well to any context where AI interacts with sensitive human experiences and data.
'''Standards for Biometric and Sensitive Data'''
[https://www.iso.org/standard/27001 ISO/IEC 27001] - Information Security Management
This international standard provides a framework for data security, emphasizing the need for strict measures to protect sensitive and biometric data (e.g., eye-tracking or heart rate data). For XR studies, adhering to ISO/IEC 27001 can ensure secure handling of biometric data.
[https://www.iso.org/committee/6794475.html <span lang="FR">ISO/IEC JTC 1/SC 42</span>] <span lang="FR">- Artificial Intelligence Standards</span>
This series of standards focuses on AI, including the use of biometric and biometric-enhancing technologies. Following these standards can help manage risks associated with XR’s use of biometric data, ensuring data accuracy, protection, and responsible use.
'''Digital Accessibility Standards'''
[https://social.desa.un.org/issues/disability/crpd/convention-on-the-rights-of-persons-with-disabilities-crpd UN Convention on the Rights of Persons with Disabilities (CRPD)]
This convention calls for inclusive access to technology, which applies to XR environments. Researchers must ensure that XR experiences are accessible to individuals with disabilities, including provisions for visual, auditory, or mobility-related needs.
[https://www.w3.org/TR/WCAG21/ Web Content Accessibility Guidelines (WCAG)]
Although focused on web content, WCAG principles are increasingly applied to XR to ensure that immersive environments are accessible. Following these guidelines can ensure that XR experiences are inclusive and provide equitable access to all participants.
'''Guidelines and Regulations'''
In Europe, biobanking is governed by regulations in the [https://health.ec.europa.eu/medicinal-products/clinical-trials/clinical-trials-regulation-eu-no-5362014_en? European Union's Clinical Trials Regulation] and the [https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=celex%3A32004L0023 Human Tissue and Cells Directive] which provides guidelines for sample collection, storage, and ethical considerations. Guideline 8 in [https://cioms.ch/wp-content/uploads/2017/01/WEB-CIOMS-EthicalGuidelines.pdf? CIOMS International ethical guidelines for health-related research involving humans] sets out recommended practices for the collection, storage and use of biological materials and related data. Also relevant is the [https://commission.europa.eu/law/law-topic/data-protection/legal-framework-eu-data-protection_en General Data Protection Regulation] (GDPR), which addresses the processing of personal data.
[https://www.isber.org/page/BPR? The International Society for Biological and Environmental Repositories] (ISBER) provides guidelines for best practices, and the [https://www.bbmri-eric.eu/library/oecd-guidelines-for-human-biobanks-and-genetic-research-databases-hbgrds-2009/? OECD's Guidelines on Human Biobanks and Genetic Research Databases] offer international recommendations. [https://pmc.ncbi.nlm.nih.gov/articles/PMC9357355/? Multiple national and regional regulations] further shape biobanking practices worldwide, emphasising ethical, legal, and privacy considerations.
It is important to remember that different guidelines and regulations will apply to biobanks and related research projects in order to comply with the requirements of different institutions, organisations and geographical locations. The further resources section lists and provides links to other relevant EU or international guidelines or standards related to biobanking in health and healthcare, but you may need to explore further afield to locate those that apply to different situations.
Make a note of which regulations and/or guidelines relating to the use biobanking are most relevant to your institution/geographical location.
[[File:Influence text.png|center|frameless|600x600px]]
Describing an image may seem like a simple cognitive activity. However, our impressions of an image or any other resource are influenced by a wide range of factors, including those listed by Fook (2006). Engaging in critical reflection through developing the habit of noticing our reactions, and recognising where they come, from will enable a greater awareness of our own assumptions. In the above activity, you have engaged with the first stage two components of critical reflection as described by Fook (2006). In the next section of the module, we explore a model to aid Fook’s second stage third and fourth components of re-evaluation and reworking of concepts and practice based on critical reflection and analysis. +
[[File:S4.png|center|frameless|600x600px]]
You can try these questions to see whether your learning from this module addresses the intended learning outcomes. No one else will see your answers. No personal data is collected. +
[[File:Ext.Image15.png|center|frameless|600x600px]]
'''Video Transcript'''
If we think about fairness and equity, I would say, then we take a little bit of a different perspective also on extended reality, because manipulation is one aspect, but let's not forget that extended reality is still a three-dimensional technology. And not everyone can use three-dimensional technology for a simple reason. That we have a certain percentage of the population, it's not very high, but still it's significant. I believe it's around 4% or 5% that they do not have a depth vision, let's say.
So, for these people, the use of extended reality is impossible basically. But then we have a big number of people, we don't have a lot of research yet to know exact numbers, that they simply find extended reality too confusing, too nauseatic. They cannot function well. So, all these people, whatever the percentage is, but it's definitely a significant minority, are not able to benefit from extended reality. Even more so they are averse to it. So that means that we have a percentage of the population that cannot use extended reality and will be left behind so far as extended reality is used widely for many reasons. For example, for training, for education, and so on and so forth. +
Research must not compromise public health responses. In particular, the involvement of clinical staff in research should not affect patient care negatively. +
In this lecture, Søren Holm outlines various practices to prevent research malpractice in Open Science. The first section of the lecture covers methods to avoid malpractice with open data, open code, and open materials and research sites. The second section examines Open Science beyond data and across borders. Lastly, the third section explores whether improved peer review practices can address issues related to research malpractice in Open Science.
'''Watch the lecture and then answer the questions.'''
'''Further reading:'''
Kingsley, D. (2025, March 30). Show your working: How the ‘open science’ movement tackles scientific misconduct. The Conversation. http://theconversation.com/show-your-working-how-the-open-science-movement-tackles-scientific-misconduct-249020
Mabile, L., Shmagun, H., Erdmann, C., Cambon-Thomsen, A., Thomsen, M., & Grattarola, F. (2025). Recommendations on Open Science Rewards and Incentives: Guidance for Multiple Stakeholders in Research. Data Science Journal, 24. https://doi.org/10.5334/dsj-2025-015 +
[[File:Two peoples hands, one person comforting the other.jpg|alt=two peoples hands, one person comforting the other|center|frameless|600x600px|two peoples hands, one person comforting the other]]
Research ethics with humans presents one of the most difficult ethical challenges for a researcher. It might help to remember that research participants often provide a voluntary service to humanity and science without personal gain;they should be treated ethically in return. +
Thank you for taking this irecs module!
Your feedback is very valuable to us and will help us to improve future training materials.
We would like to ask for your opinions:
1. To improve the irecs e-learning modules
2. For research purposes to evaluate the outcomes of the irecs project
To this end we have developed a short questionnaire, which will take from 5 to 10 minutes to answer. Your anonymity is guaranteed;you won’t be asked to share identifying information or any sensitive information. Data will be handled and stored securely and will only be used for the purposes detailed above. You can find the questionnaire by clicking on the link below.
This link will take you to a new page;[https://eur01.safelinks.protection.outlook.com/?url=https%3A%2F%2Fforms.office.com%2Fe%2FK5LH08FyvQ&data=05%7C02%7CKChatfield%40uclan.ac.uk%7Cde983f54bcc64d66a02908dcd0b50ccd%7Cebf69982036b4cc4b2027aeb194c5065%7C0%7C0%7C638614723283127814%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C0%7C%7C%7C&sdata=shLTj7qPsGmGj0JOoPRZV2LhKbl5XOOhAbo7F%2FWzW7s%3D&reserved=0 https://forms.office.com/e/K5LH08FyvQ]
Thank you! +
[[File:M13..png|center|frameless|600x600px]]
Chatfield, K., Schroeder, D., Guantai, A., Bhatt, K., Bukusi, E., Adhiambo Odhiambo, J., ... & Kimani, J. (2021). Preventing ethics dumping: the challenges for Kenyan research ethics committees. Research Ethics, 17(1), 23-44. Available at: https://journals.sagepub.com/doi/full/10.1177/1747016120925064 (Free to download)
López A, Martins M, Chissico C, et al (2019) OA-87 Research ethics committees in Mozambique: operational and functional characteristics evaluated from a self-assessment tool in 2019 BMJ Global Health 2023;8:A3. https://gh.bmj.com/content/8/Suppl_10/A3.2
Schroeder, D. (2007). Benefit sharing: it’s time for a definition. Journal of medical ethics, 33(4), 205-209.
Schroeder, D., & Pisupati, B. (2010). Ethics, justice and the convention on biological diversity. Available at: https://clok.uclan.ac.uk/9695/1/Ethics,%20Justice%20and%20the%20convention.pdf (Free to download)
Schroeder, D., Cook, J., Hirsch, F., Fenet, S., & Muthuswamy, V. (2018). Ethics dumping: case studies from north-south research collaborations. Springer Nature. Available at: https://link.springer.com/book/10.1007/978-3-319-64731-9 (Free to download)
Schroeder, D., Chatfield, K., Singh, M., Chennells, R., & Herissone-Kelly, P. (2019). Equitable research partnerships: a global code of conduct to counter ethics dumping (p. 122). Springer Nature. Available at: https://link.springer.com/book/10.1007/978-3-030-15745-6 (Free to download)
Schroeder, D., Chatfield, K., Muthuswamy, V., & Kumar, N. K. (2021). Ethics Dumping–How not to do research in resource-poor settings. Journal of Academics Stand Against Poverty, 1(1), 32-55. Available at: https://journalasap.org/index.php/asap/article/view/4 (Free to download)
Wynberg, R., Schroeder, D., & Chennells, R. (2009). Indigenous peoples, consent and benefit sharing: lessons from the San-Hoodia case (Vol. 15). Berlin: Springer.
'''Research ethics codes'''
The San Code of Research Ethics, available from: https://www.globalcodeofconduct.org/affiliated-codes/
The TRUST Global Code of Conduct for Equitable Research Partnerships, available from: https://www.globalcodeofconduct.org/the-code/
'''Videos'''
AI and Ethics Dumping: A 25-minute module delivered by Professor Doris Schroeder https://youtu.be/F381tg_upUc?si=FzqE2qOYqpT7TPJa
More videos can be found here: https://www.youtube.com/@trustandprepared1000
'''Useful websites'''
The African Society of Human Genetics https://www.afshg.org/
National Commission for Science, Technology and Innovation – (NACOSTI) – Kenya [https://www.nacosti.go.ke/ nacosti.go.ke]
NACOSTI page on Tanzania -https://nsec.nacosti.go.ke/tanzania/
Tanzania Commission for Science and Technology - https://www.costech.or.tz/
Uganda National Council for Science and Technology (UNCST) Research Committee Accreditation https://www.uncst.go.ug/details.php?option=smenu&id=9&Research%20Ethics%20Committee%20Acreditation.html
The Science for Africa Foundation https://scienceforafrica.foundation/
TRUST (2018) The TRUST Code – A Global Code of Conduct for Equitable Research Partnerships, DOI: https://doi.org/10.48508/GCC/2018.05
'''Further resources on AI technologies'''
Alford A, Rathod N (2022) AI could worsen health inequities for UK’s minority ethnic groups - new report 22 February 2022 Imperial News. Imperial College London. Available at: [https://www.imperial.ac.uk/news/230413/ai-could-worsen-health-inequities-uks/  https://www.imperial.ac.uk/news/230413/ai-could-worsen-health-inequitie…];Colón-Rodríguez CJ (2023) Shedding Light on Healthcare Algorithmic and Artificial Intelligence Bias US. Department of Office of Minority Health. Available at: [https://minorityhealth.hhs.gov/news/shedding-Light-healthcare-algorithmic-and-artificial-intelLigence-bias https://minorityhealth.hhs.gov/news/shedding-Light-healthcare-algorithm…]
Morley J, Machado CCV, Burr C, Cowls J, Joshi I, Taddeo M, Floridi L. (2020) The ethics of AI in health care: A mapping review Soc Sci Med. 2020 Sep;260:113172. doi: 10.1016/j.socscimed.2020.113172. Epub 2020 Jul 15. PMID: 32702587. Available at: https://pubmed.ncbi.nlm.nih.gov/32702587/ '"`UNIQ--nowiki-0000000B-QINU`"';Resseguier, Anaïs & Ufert, Fabienne (2024). AI research ethics is in its infancy: the EU’s AI Act can make it a grown-up. Research Ethics 20 (2):143-155. https://philpapers.org/rec/RESARE
==='''Relevant guidelines and policies'''===
''It is important to remember that different guidelines and regulations will apply to research projects in order to comply with the requirements of different institutions, organisations and geographical locations. Listed here are the current most relevant EU or international guidelines or standards related to AI in health and healthcare, but you may need to explore further afield to locate those that apply to different situations.''
Medical Diagnosis and Artificial Intelligence: Ethical Issues. Joint opinion of the CCNE and CNPEN,
CCNE Opinion 141, CNPEN Opinion 4. November 2022
https://www.ccne-ethique.fr/sites/default/files/2023-05/Opinion%20No.141.pdf
'''''Council of Europe:'''''
Guidelines on artificial intelligence and data protection (2019)
https://ec.europa.eu/info/funding-tenders/opportunities/docs/2021- [https://ec.europa.eu/info/funding-tenders/opportunities/docs/2021-2027/horizon/guidance/ethics-by-design-and-ethics-of-use-approaches-for-artificial-intelligence_he_en.pdf 2027/horizon/guidance/ethics-by-design-and-ethics-of-use-approaches-] [https://ec.europa.eu/info/funding-tenders/opportunities/docs/2021-2027/horizon/guidance/ethics-by-design-and-ethics-of-use-approaches-for-artificial-intelligence_he_en.pdf for-artificial-intelLigence_he_en.pdf]
'''''Deutscher Ethikrat (German Ethics Council):'''''
Opinion: Humans and Machines – Challenges of Artificial Intelligence (2023) https://www.ethikrat.org/en/publications/opinions/humans-and-machines/ (currently only available in German, an English translation will be available in due course)
'''''European Commission:'''''
Ethics By Design and Ethics of Use Approaches for Artificial Intelligence (2021)
https://ec.europa.eu/info/funding-tenders/opportunities/docs/2021-2027/horizon/guidance/ethics-by-design-and-ethics-of-use-approaches-for-artificial-intelligence_he_en.pdf
'''Ethics guidelines for trustworthy AI (2019)'''
[https://digital-strategy.ec.europa.eu/en/library/ethics-guidelines- https://digital-strategy.ec.europa.eu/en/Library/ethics-guideLines-] [https://digital-strategy.ec.europa.eu/en/library/ethics-guidelines-trustworthy-ai trustworthy-ai]
'''''OECD Legal Instruments'''''
Recommendation of the Council on Artificial Intelligence (2019)
[https://legalinstruments.oecd.org/en/instruments/oecd-legal-0449 https://legaLinstruments.oecd.org/en/instruments/oecd-legal-0449]
'''''UNESCO:'''''
Recommendations on the Ethics of Artificial Intelligence (2022)
https://unesdoc.unesco.org/ark:/48223/pf0000381137
'''''World Health Organisation:'''''
Ethics and governance of artificial intelligence for health (2021)
[[File:Ge3Image11.png|center|frameless|600x600px]]
Genome editing: and ethical review, Nuffield Council on Bioethics 2016, Available at: [https://www.nuffieldbioethics.org/assets/pdfs/Genome-editing-an-ethical-review.pdf https://www.nuffieldbioethics.org/assets/pdfs/Genome-editing-an-ethical…]
How gene drive works, Target Malaria, available at: https://targetmalaria.org/what-we-do/how-it-works/ '"`UNIQ--nowiki-00000000-QINU`"';Garrood WT, Cuber P, Willis K, Bernardini F, Page NM, Haghighat-Khah RE (2022) Driving down malaria transmission with engineered gene drives. Frontiers in Genetics, 19(13) :891218. Available at: https://www.frontiersin.org/articles/10.3389/fgene.2022.891218/full '"`UNIQ--nowiki-00000001-QINU`"';Hartley S, Smith RDJ, Kokotovich A et al. (2021) Ugandan stakeholder hopes and concerns about gene drive mosquitoes for malaria control: new directions for gene drive risk governance, Malar J 20: 149. https://doi.org/10.1186/s12936-021-03682-6
Nolan, T (2021) Control of malaria-transmitting mosquitoes using gene drives, Phil. Trans. R. Soc. B37620190803 http://doi.org/10.1098/rstb.2019.0803
Saey, TH (2022) Who decides whether to use gene drives against malaria-carrying mosquitoes?, Science News, available at: [https://www.sciencenews.org/article/gene-drives-mosquito-malaria-crispr-africa-public-outreach https://www.sciencenews.org/article/gene-drives-mosquito-malaria-crispr…]
Then C (2016) European patent granted on genetically engineered insects, available at: [https://www.testbiotech.org/en/news/european-patent-granted-genetically-engineered-insects https://www.testbiotech.org/en/news/european-patent-granted-genetically…] +
With the increasing pressure on (young) researchers to publish, there is a growing concern over the proliferation of fake papers within the academic community. In science and research, a "''paper mill''" refers to a deceptive practice where manuscripts are fabricated or manipulated and then submitted to academic journals for publication.
==== What is a paper mill? ====
The [https://publicationethics.org/sites/default/files/paper-mills-cope-stm-research-report.pdf Committee on Publication Ethics] defines paper mills as "the process by which manufactured manuscripts are submitted to a journal for a fee on behalf of researchers with the purpose of providing an easy publication for them, or to offer authorship for sale."
These manuscripts are often generated for the purpose of exploiting the academic publishing system, typically to boost publication records or to fulfill requirements for academic advancement, such as obtaining tenure or securing funding. Fake papers can be identified both during the submission process and after publication.
Paper mills may involve the use of ghostwriters, falsified data, or plagiarized content. This unethical practice undermines the integrity of scholarly publishing and can have serious consequences for academic credibility and scientific progress.
=== Paper mills in the era of large language models (LLMs) ===
The emergence of large language models (LLMs) such as ChatGPT has raised concerns about an increase in paper mills. These tools can quickly generate fake papers and authorships, posing a significant threat to scientific publishing by blurring the line between genuine and fabricated research.
This underscores worries in the scientific community about maintaining integrity in scholarly publishing and preventing the misuse of AI technology. It's crucial to recognize that attempting to pass off AI-generated text as one's own work constitutes plagiarism and academic dishonesty.
Reading for fun:
[https://publicationethics.org/resources/research/paper-mills-research Paper Mills Research report from COPE & STM]
Van Noorden, R. (2023). How big is science’s fake-paper problem? An unpublished analysis suggests that there are hundreds of thousands of bogus ‘paper-mill’ articles lurking in the literature. Nature, 623, 466-467. https://doi.org/10.1038/d41586-023-03464-x
[1] COPE & STM. Paper Mills — Research report from COPE & STM. https://doi.org/10.24318/jtbG8IHL
'''Questions to consider:'''
* Are we involving participants in research activities that relate directly to environmental or climate conditions in their local context (e.g., observations, monitoring, interpretation of change)?
* Do participatory roles allow contributors to share context-specific environmental knowledge, lived experience, or observations that may not be captured through technical data alone?
* Are we informing participants about how their contributions relate to environmental or climate questions addressed by the research, including how data will be used, shared (e.g., as open data where applicable, or generalised/withheld where precise information could cause environmental harm), and interpreted?
* Are appropriate support, feedback, or training provided to enable meaningful participation in environmentally or climate-relevant research activities?
'''Example :''' A project collects environmental observations through a citizen science platform but limits participant involvement to data submission, without explaining how observations contribute to understanding local environmental change. Reflecting on participation in practice highlights whether participants could be more meaningfully engaged through feedback, shared interpretation of results, or contextual discussion of environmental trends. +
[[File:Mm15.png|center|frameless|600x600px]]
'''Equality'''
Equality implies that people are treated equally in terms of rights, or access to services etc. without discrimination or unfair advantage. In the context of social justice and human rights, equality involves equal access to resources and opportunities, as well as ensuring that individuals are not disadvantaged or marginalised. This can include efforts to address systemic inequalities, discrimination, and barriers to full participation in society.
'''Equity'''
Equity refers to fairness in the distribution of resources, opportunities, and rights. It involves ensuring that everyone has access to what they need to thrive and reach their full potential, regardless of their background, identity, or circumstances. Unlike equality, which aims to treat everyone the same, equity recognizes that different individuals or groups may require different levels of support or resources to achieve equal outcomes.
[[File:Mm16.png|center|frameless|600x600px]]
'''Intellectual property rights'''
Intellectual property rights (IPR) refer to the legal rights granted to individuals or entities to protect their creations or inventions, which can include inventions, literary and artistic works, designs, symbols, names, and images used in commerce. These rights typically include patents, copyrights, trademarks, and trade secrets, granting creators or owners exclusive rights to use and control their intellectual property for a specified period. These rights enable individuals and organizations to benefit financially from their innovations and creativity while fostering innovation and creativity by providing incentives for research, development, and investment.
'''Traditional knowledge'''
Traditional knowledge encompasses the accumulated wisdom, practices, and innovations passed down through generations within a specific culture or community. It includes knowledge about the natural environment, biodiversity, agricultural practices, healing methods, cultural expressions, and other aspects of traditional lifestyles. Traditional knowledge is often orally transmitted and deeply rooted in local customs, beliefs, and experiences. It plays a vital role in sustainable development, biodiversity conservation, and the preservation of cultural heritage.
[[File:Question mark in speech bubble.jpg|alt=question mark in speech bubble|center|frameless|600x600px|question mark in speech bubble]]
You can try these questions to see whether your learning from this module addresses the intended learning outcomes. No one else will see your answers. No personal data is collected. +
