Digital technologies have positively transformed society, but they have also led to undesirable consequences not anticipated at the time of design or development. We posit that insights into past undesirable consequences can help researchers and practitioners gain awareness and anticipate potential adverse effects. To test this assumption, we introduce BLIP, a system that extracts real-world undesirable consequences of technology from online articles, summarizes and categorizes them, and presents them in an interactive, web-based interface. In two user studies with 15 researchers in various computer science disciplines, we found that BLIP substantially increased the number and diversity of undesirable consequences they could list in comparison to relying on prior knowledge or searching online. Moreover, BLIP helped them identify undesirable consequences relevant to their ongoing projects, made them aware of undesirable consequences they "had never considered," and inspired them to reflect on their own experiences with technology.

It all started in 1950 when philosopher and mathematician Alan Turing revisited the question of whether machines (or computers) can "think." This question was tackled by the early modern philosopher René Descartes, who argued that because thinking is a mental activity, physical bodies cannot think, thus ruling out that machines can think. Turing came up with an idea for testing whether machines can think, the so-called Turing Test, which would analyze the speech patterns of answers provided by machines in response to everyday questions. IBM spent over $62 million to create a Watson for Oncology, an AI oncology expert adviser that uses AI algorithms to recommend cancer treatment. While machines cannot think the way humans do, they do sometimes make their own surprising "decisions."