Texas School of Information Associate Professor Ken Fleischmann received a $100,000 grant from the Legal Implications for IoT, Machine Learning, and Artificial Intelligence Systems program, Cisco Research Center, for "Field Research with Policy, Legal, and Technological Experts about Transparency, Trust, and Agency in Machine Learning." The Cisco Research Center connects researchers and developers from Cisco, academia, governments, customers, and industry partners with the goal of facilitating collaboration and exploration of new and promising technologies.
The request for proposals (RFP 16-02) invited researchers to investigate legal and policy issues in the quickly developing world of machine learning (ML), artificial intelligence (AI), machine-to-machine interactions, and the rapidly expanding world of data creation, transfer, collection, and analysis from Internet of Things (IoT).
The project’s principal investigators, Dr. Fleischmann and Sherri Greenberg of the LBJ School of Public Affairs, explain that while machine learning has the potential to revolutionize society, transform how we do business, defend our homeland, and heal diseases, it also raises numerous ethical challenges, which our legal and political systems are largely ill-equipped to deal with. In their proposal, they ask: “How can we ensure that ML experts are aware of the ethical, political, and legal implications of ML, and that policy experts and legal scholars are up to date in their understanding of ML and its potential societal implications?”
According to Fleischmann, the project’s goal is to “bridge the gap in expertise among technology experts and legal and policy experts.” On one hand, this involves helping legal and policy experts to understand the limits of technology, both at present and (our best projection of what will be possible) ten years down the road, and on the other, helping technology experts to understand the legal and policy implications of their work,” said Fleischmann.
Fleischmann explains that this project can lead to insights that enhance the academic education and workplace training of technologists, as well as legal and policy scholars in future research. Not only does it have the potential “to help educate and prepare ML researchers and developers about the potential ethical, legal, and policy implications of their work, but it will also help prepare future policy makers and legislators about how to regulate and legislate to ensure safe and efficient use of ML.”