In recent times, there have been stricter rules on harassment, bullying and violence rules formulated by Search engines and social media platforms. The recent scrutiny placed on national security and privacy have helped internet companies up the ante and crack down on hateful content, fake news, and malicious actors.
The mayor of New York City, Bill de Blasio will decide whether or not to sign a local bill on agency use of “automated decision systems,” according to NYC public records. These systems are “computerized implementations of algorithms” using ML, AI or data processing that make or help with decision making. The bill calls for a task force to oversee and recommend how agencies use these algorithms and how to address discrimination or harm at the hands of these algorithms.
As shown by the NYC bill, it is not enough to monitor the contents; these platforms need to scrutinize what goes on in the backstage. Big Data and AI have started to run the show, and algorithms have started identifying a company’s inefficiencies to law enforcement and customized consumer interface applications.
Biases in the AI systems are introduced during the development, as the systems learns or during application from a variety of sources. These biased data sets can cause different problems, such as the lack of diversities among programmers developing the AI system.
Issues such as racial, gender or ethnic discrimination arises when a major city like NYC or a major organization like Facebook uses biased algorithm. Lawmakers from the federal to the local level are struggling with these potential biases in technologies that are still largely unregulated.
The opinion of various experts in the industry is that the best way to deal with these problems is by handling the issues over to the enterprise and avoiding ham-fisted government oversight. Under this framework, the reactive rules formulated by the enterprise will address problems as they arise, whereas regulations that are proactive would slow down the development of technology and reduce investment.