How helping students design ethical metaverse platforms can lead to safety and well being for all
Notice bibliographique
Résumé
A lack of proximity and enhanced anonymity in virtual worlds seems to provide the license to Artificial Intelligence (AI) based metaverse users to misbehave. Bullying, abuse, spread of hatred and divisiveness and manipulations of minds in Metaverses are growing exponentially due to the speed and magnitude with which AI enabled bots in Metaverses can multiply and reproduce content. Online violence has begun spilling into the real world which is negatively impacting the psyche and wellbeing of children and young adults in society. Ethicists or well-meaning employees have spoken out against these violations in Metaverses. But we find many such ethics groups have been dissolved or silenced while employees who are whistleblowers are often fired, discredited, or dismissed. Business Ethics, Marketing, Management and Sustainability students are often asked to simply carry out an ethical analysis of cases and provide recommendations. While such processes have helped explore various ethical schools of thought, the application of these concepts to AI based metaverses seems less about what framework to apply and more about how to design a fail-proof system to protect the safety and wellbeing of all. Such an approach will make students more aware of the consequences of their choices and develop a sense of responsibility towards the wellbeing of all. The paper proposes the use of a case study of a hypothetical company that has a metaverse platform and the challenges it faces in addressing abuse and scandals on its platform. The paper also offers a detailed review along with the pros and cons of several ethical frameworks and puts forth two key questions to students asking them to design a metaverse platform that can, a) ensure the wellbeing, security, and safety of the users who are not even aware that their minds may be swayed and manipulated; and b) find a way to convince companies that create AI-based metaverses to adopt ethical frameworks. Sample answers are provided to help faculty work with students understand the importance of always designing products and services with personal and others’ well-being in mind rather than only making profits at the cost of people’s safety and security.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,005 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».