Nathan E. Sanders is a data scientist and fellow at the Berkman Klein Center at Harvard University. Bruce Schneier is a security technologist, researcher, and faculty member at the Harvard Kennedy School.
Lobbying has long been part of the interaction between politicians and advocates seeking to balance their competing interests, but some corporate organizations are adept at using legal but underhanded strategies to bend the rules in their favor.
Artificial intelligence tools can make such sneaky strategies more common and effective. A natural opening for this technology is micro-legislation, a term for small pieces of proposed law that serve narrow interests.
Computer models can predict the likely fate of proposed legislative amendments, as well as the ways in which lobbyists can most effectively deliver the desired results, a critical part of building an artificial intelligence lobbyist.
The danger of micro-legislation—a danger greatly amplified by artificial intelligence—is that it can be used in ways that make it difficult to understand who the legislation really benefits. Read the story in its entirety.
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