Abstract
Big Data and Artificial Intelligence have a symbiotic relationship. Artificial Intelligence needs to be trained on Big Data to be accurate, and Big Data's value is largely realized through its use by Artificial Intelligence. As a result, Big Data and Artificial Intelligence practices are tightly intertwined in real life settings, as are their impacts on society. Unethical uses of Artificial Intelligence are therefore a Big Data problem, at least to some degree. Efforts to address this problem have been dominated by the documentation of Ethical Artificial Intelligence principles and the creation of technical tools that address specific aspects of those principles. However, there is mounting evidence that Ethical Artificial Intelligence principles and technical tools have little impact on the Artificial Intelligence that is created in practice, sometimes in very public ways. The goal of this commentary is to highlight four interconnected areas society can invest in to close this Ethical Artificial Intelligence publication-to-practice gap, maximizing the positive impact Artificial Intelligence and Big Data have on society. For Ethical Artificial Intelligence to become a reality, I argue that these areas need to be addressed holistically in a way that acknowledges their interdependencies. Progress will require iteration, compromise, and transdisciplinary collaboration, but the result of our investments will be the realization of Artificial Intelligence's and Big Data's tremendous potential for social good, in practice rather than in just our hopes and aspirations.
Highlights
Calls for Ethical Artificial Intelligence (AI) are increasingly urgent
Even after a first wave of responses coalesced around Ethical AI principles (Hickok, 2021), a second wave cultivated Ethical AI technical tools, and a third wave is motivating litigation and advocacy (Kind, 2020), published Ethical AI principles and technical tools still have limited impact on the daily practices of AI users and producers (Schiff et al, 2021; Vakkuri et al, 2020)
Even if qualified members do exist on an AI product team, they are usually not afforded the time or financial resources to do the experimentation, research, and monitoring that would be required to bring the implementation of technical Ethical AI tools to fruition (Rakova et al, 2021)
Summary
Calls for Ethical Artificial Intelligence (AI) are increasingly urgent. Yet even after a first wave of responses coalesced around Ethical AI principles (Hickok, 2021), a second wave cultivated Ethical AI technical tools, and a third wave is motivating litigation and advocacy (Kind, 2020), published Ethical AI principles and technical tools still have limited impact on the daily practices of AI users and producers (Schiff et al, 2021; Vakkuri et al, 2020). Many technical tools are available to help mitigate AIrelated ethical challenges, but AI product teams report not having adequate access to them (Rakova et al, 2021; Schiff et al, 2021; Vakkuri et al, 2020).
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