#RSAC: Time to Take Action on AI-Enabled Electoral Vote Influencing
In a talk at the RSA Conference in San Francisco, students and researchers from University of California, Berkeley presented a theoretical method on how voters could be influenced using technical and automated methods.
Talking about “How AI Inference Threats Might Influence the Outcome of 2020 Election,” the three presented their own research, which included aggregating data to show how misinformation can be spread. Karel Baloun, software architect and entrepreneur at UC Berkeley, said these types of attacks can be nefarious as “attacks on democracy” are often not seen and it can be denied that they took place.
Pointing at the 2016 US presidential election, Baloun said that the hacking of the Democrats’ emails by Russia and passing of them to WikiLeaks “set the narrative for the election” and there is proof that this effort was able to “suppress over 100,000 votes.” He said that there are four examples of elections that have been influenced in history:
The 2016 UK Brexit vote on EU Membership
The 2019 Hong Kong Anti-Extradition Law Protests
The 2020 Taiwan Presidential Election
Ken Chang, cybersecurity researcher at University of California, Berkeley, said that when someone registers to vote, that information should be trusted to be held securely, as all information that is collected is “a critical piece of information.”
With voter registration data, Chang said that the potential of a data breach is obvious, so the conversation needs to be centered on how to protect information, and not on ..
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