Original article was published by The Unlikely Techie on Artificial Intelligence on Medium
We Need Diverse AI Ethics Boards
Let’s make room for more perspectives on AI Ethics. For the benefit of us all.
How globally diverse are AI Ethics boards? An article published by MIT shows that most seats on these boards are occupied by Americans and Europeans. If these compositions remain like this, we run the risk that bias in AI will perpetaute.
An excellent example of different views can be seen in the question of what intelligence is. While we can’t scientifically explain what intelligence is, there are vastly different perceptions of how intelligent behavior expresses itself. While in Western societies, intelligence is the one who can respond quickly, in other cultures, it is the one who can give the most balanced and considered answer. In this interpretation of intelligence, it does not speed that matters, but the response in and of itself. What do you find more intelligent?
AI frameworks have caused issues that excessively influenced marginalized groups, whereas profiting an advantaged few. Today’s worldwide AI moral endeavors aim to assist everybody in this innovation and avoid it from causing harm. For the most part, AI ethics counsels and groups try to achieve this by making rules and standards for engineers, funders, and controllers. But the different interpretations of intelligence, morals, and ethics are, if not balanced, construed in favor of already dominant world-views. Studies show that views from Western Europe and North America prevail and thus inherently show prejudice. In their paper, Global AI Ethics: A Review of the Social Impacts and Ethical Implications of Artificial Intelligence, Alexa Hagerty and Igor Rubinov state that “current analyses of AI in a global context are biased toward perspectives held in the U.S., and limited by a lack of research, especially outside the U.S. and Western Europe.”
Abhishek Gupta and Victoria Health support this: “This lack of regional diversity reflects the current concentration of AI research (pdf): 86% of papers published at AI conferences in 2018 were attributed to authors in East Asia, North America, or Europe. And fewer than 10% of references listed in AI papers published in these regions are to pieces from another region. Patents are also highly concentrated: 51% of AI patents published in 2018 were attributed to North America.”
The Personal Is the Political and Algorithms Are Opinions
In this context, it is also essential to show that social views can differ, but that this can be broken down to the individual. Gupta and Health state that:
“‘Fairness,’ ‘privacy,’ and ‘bias’ mean different things (pdf) in different places. People also have disparate expectations of these concepts depending on their own political, social, and economic realities. The challenges and risks posed by AI also differ depending on one’s locale.”
There are projects, especially regarding autonomous driving and the ethical dilemmas that come with it, to crowdsource human morality. By crowdsourcing solutions to moral dilemmas from millions of humans, scientists and engineers hope to train machines more effectively (e.g., MIT’s Moral Machine). Therefore, companies working on ethical guidelines for AI-powered systems and tools need to engage users worldwide to help create appropriate standards to govern these systems.
Furthermore, they must also be aware of how their policies apply in different contexts. In the paper, Art Impact AI: Observations and Strategic Recommendations, Valentine Goddard states that it is “important figure out best practices as we deploy AI technologies in geographical locations with different values, protocols, laws, and highly varying concepts of what is ethical or not.”
Bringing Together Different Perspectives From All Parts of the Globe
To prevent history from repeating itself, and to ensure that disturbing historically grown developments do not advance, different perspectives, realities, and views of life must be considered in globally active AI ethical considerations.
According to Gupta and Health, the newly formed Global AI Ethics Consortium “has no founding members representing academic institutions or research centers from the Middle East, Africa, or Latin America. This omission is a stark example of colonial patterns (pdf) repeating themselves.” On the other hand, there are, however, efforts to have recommended changes to visa laws and proposed policies to facilitate researchers’ travel. There is a consensus that AI advancements have to be understood, shared, and debated globally. It is only in this way that underrepresented groups can be heard. Groups such as the Partnership on AI recognize the lack of geographic diversity in AI more broadly. There is Maskhane, a grassroots organization that brings together NLP (natural-language-processing) researchers from all over Africa to support machine-translation work has ignored non-dominant languages and dialects.
Even though projects such as Maskhane show that there are efforts in the right direction, we must not forget that it is vital to include diverse perspectives into discussions about AI. All of us need to remember that regional and cultural diversity are essential to any AI ethics conversation. Or, as Valentine Goddard points out:
“Not only does AI present exciting opportunities in digital arts, and revolutionize interactive and immersive experiences, but AI needs the arts. The valued participation of artists, cultural workers, and creative agents can push AI beyond its current limits and facilitate a sustainable, human-planet-centric adoption of AI.”
It has to be our shared priority to make responsible AI the norm instead of the exception. If we commit to this, we have to learn to listen to the voices of individuals who don’t already hold power and influence.