Recommendations

Recommendations for a Responsible Future with Machine Learning

The establishment of professional organizations to help govern standards for A.I. technologies in knowledge institutions such as universities, libraries, and museums would ensure that ethical considerations are always in place. These organizations would need to be respected by all types of institutions but exist directly above as a managing entity. This will help the emerging field of AI as a whole become more ethical (Jo & Gebru, 2020). We can also encourage ethical consideration and promote accountability in our institutions by requiring a mission statement, which includes artificial intelligence technology considerations, that is public facing to be created (Jo & Gebru, 2020).

In 2018, Amnesty International produced a The Toronto Declaration, a document detailing a list of standards for non-discrimination and equality practices in machine learning systems, reaffirming human rights as artificial intelligence technologies continue to grow in use (Toronto Declaration, 2018). The human element must not be underestimated when dealing with artificial intelligence technologies. Humans must continue to tirelessly provide oversight, checking machine learning algorithms and their outputs for errors, bias, discrimination, racism, and otherwise antisocial products (Candela & Carrasco, 2022). Perhaps the most important lesson we can learn from artificial intelligence is the great need for empathy in libraries today.

References

Candela, G., & Carrasco, R. C. (2022). Discovering emerging topics in textual corpora of galleries, libraries, archives, and museums institutions. Journal of the American Society for Information Science and Technology, 73(6), 820-833. doi:10.1002/asi.24583

Jo, E., & Gebru, T. (2020). Lessons from archives: Strategies for collecting sociocultural data in machine learning. Paper presented at the 306-316. doi:10.1145/3351095.3372829

The Toronto Declaration: Protecting the Rights to Equality and Non-discrimination in Machine Learning Systems. (2018). In Policy File. Amnesty International.