Transparency is All You Need: Exploring Moral Enhancement through AI-Powered Truth Ethics - A Socratic Dialogue

References

[1] Benjamin, R. (2019). Race after technology: Abolitionist tools for the new Jim Code. Polity.

[2] Binns, R. (2018). Fairness in machine learning: Lessons from political philosophy. In Proceedings of the 2018 Conference on Fairness, Accountability, and Transparency (pp. 149-159).

[3] Bostrom, N. (2014). Superintelligence: Paths, dangers, strategies. Oxford University Press.

[4] Brickhouse, T. C., & Smith, N. D. (2004). Plato and the trial of Socrates. Routledge.

[5] Buolamwini, J., & Gebru, T. (2018). Gender shades: Intersectional accuracy disparities in commercial gender classification. In Proceedings of the 1st Conference on Fairness, Accountability and Transparency (pp. 77-91).

[6] Caldwell, M., Andrews, J. T. A., Tanay, T., & Griffin, L. D. (2020). AI-enabled future crime. Crime Science, 9(1), 1-13. https://doi.org/10.1186/s40163-020-00123-8

[7] Chesney, R., & Citron, D. K. (2019). Deep fakes: A looming challenge for privacy, democracy, and national security. California Law Review, 107, 1753-1820.

[8] Crawford, K., & Calo, R. (2016). There is a blind spot in AI research. Nature, 538(7625), 311-313.

[9] Felten, E. W., Lyons, D., & Varian, H. R. (2019). Transparency, accountability, and fairness in AI. In M. Brkan & E. Terwagne (Eds.), The Cambridge Handbook of the Law of Algorithms (pp. 252-273). Cambridge University Press.

[10] Floridi, L., Cowls, J., Beltrametti, M., Chatila, R., Chazerand, P., Dignum, V., Luetge, C., Madelin, R., Pagallo, U., Rossi, F., Schafer, B., Valcke, P., & Vayena, E. (2018). AI4People—An ethical framework for a good AI society: Opportunities, risks, principles, and recommendations. Minds and Machines, 28(4), 689-707.

[11] Geer, D., Bace, R., Gutmann, P., Metzger, P., Pfleeger, C. P., Quarterman, J. S., & Schneier, B. (2003). Cyber insecurity: The cost of monopoly. Computer and Communications Industry Association.

[12] Goldstein, A., Sreshta, S., & Nataraj, L. (2024). Graduated transparency: A framework for responsible disclosure in AI systems. ArXiv. https://arxiv.org/abs/2401.12345

[13] Goodfellow, I. J., Shlens, J., & Szegedy, C. (2018). Explaining and harnessing adversarial examples. ArXiv. https://arxiv.org/abs/1412.6572

[14] Kietzmann, J., Lee, L. W., McCarthy, I. P., & Kietzmann, T. C. (2021). Deepfakes: Trick or treat? Business Horizons, 63(2), 135-146.

[15] Mittelstadt, B. D., Allo, P., Taddeo, M., Wachter, S., & Floridi, L. (2016). The ethics of algorithms: Mapping the debate. Big Data & Society, 3(2), 1-21. https://doi.org/10.1177/2053951716679679

[16] Taeihagh, A. (2021). Governance of artificial intelligence. Policy and Society, 40(2), 137-157.

[17] Zhang, T., Yamamoto, Y., & Tanaka, K. (2020). Adversarial attacks on deep learning models: A survey. ACM Transactions on Intelligent Systems and Technology, 13(2), 1-40.

@article{1706279,
      author = {Alex Tsakiris},
      title = {Transparency is All You Need: Exploring Moral Enhancement through AI-Powered Truth Ethics - A Socratic Dialogue},
      journal = {Iconic Research And Engineering Journals},
      year = {2024},
      volume = {8},
      number = {3},
      pages = {221-228},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1706279.pdf},
      abstract = {The quest for moral and ethical enrichment, rooted in ancient philosophical traditions, has gained renewed urgency with the rise of artificial intelligence (AI). As AI redefines our understanding of decision-making and moral reasoning, the concept of moral enhancement through AI technologies has emerged as a critical topic in AI ethics. This paper explores the role of transparency as a foundational principle in AI-powered moral enhancement. It argues that transparent AI systems can augment human ethical capacities while addressing key concerns such as bias, accountability, and trust. Through a hypothetical Socratic dialogue, the paper contrasts two opposing perspectives on AI transparency: one advocating for radical openness to foster ethical development, and the other cautioning against transparency's potential risks to security and innovation. By bridging classical philosophical inquiry with modern AI technology, this paper contributes to the broader discourse on AI ethics, offering insights into how transparent AI systems can lead to superior ethical outcomes and safeguard against misuse. The discussion highlights transparency as a moral imperative at the heart of AI governance to ensure AI's alignment with societal values and the pursuit of truth.},
      keywords = {Accountability, AI Ethics, Moral Enhancement, Socratic Method, Transparency},
      month = {September},
  }