Artificial Intelligence (AI) has become one of the biggest drivers of technological change, impacting industries and creating entirely new opportunities. From an engineering standpoint, AI is just a more advanced form of data engineering. Most good AI projects function more like muddy pickup trucks than spotless race cars — they are a workhorse technology that humbly makes a production line 5% safer or movie recommendations a little more on point. However, more so than many other technologies, it is very, very easy for a well-intentioned AI practitioner to inadvertently do harm when they set out to do good. AI has the power to amplify unfair biases, making innate biases exponentially more harmful.
AI Engineers Need to Think Beyond Engineering
Google AI practitioners argue that partnerships with social scientists and community members can deepen understanding of complex problems and lead to fairer algorithms.
October 28, 2020
Summary.
It is very, very easy for a well-intentioned AI practitioner to inadvertently do harm when they set out to do good — AI has the power to amplify unfair biases, making innate biases exponentially more harmful. Because AI often interacts with complex social systems, where correlation and causation might not be immediately clear — or even easily discernible — AI practitioners need to build partnerships with community members, stakeholders, and experts to help them better understand the world they’re interacting with and the implications of making mistakes. Community-based system dynamics (CBSD) is a promising participatory approach to understanding complex social systems that does just that.
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Excel in a world that's being continually transformed by technology.