As for much of the technology industry, 2018 has been a year to count on artificial intelligence. As AI systems are integrated into several products and services, the lack of technologies has become more apparent. Scientists, businesses and the general public have all begun to take more into the limitations of AI and their negative effects, and ask important questions such as: how is this technology used and for what benefit?
This reckoning has been most visible as a parade of negative headlines on algorithmic systems. This year saw the first deaths caused by self-driving cars; Cambridge Analytica scandal; charges that Facebook facilitates the genocide in Myanmar; the revelation that Google helped with the Pentagon train drone monitoring tool; and ethical questions about the technical giant's human-sounding AI assistant. The research group AI now described 201
But it is not necessary to see these headings as only negative. After all, a scandal is better than the evil that goes unnoticed, and controversy can in theory help us improve.
Take face recognition. This has been one of the fastest technologies in 2018, with successes like the Chinese police identifying a criminal at a music concert, and broadcasting services using technology to identify guests at royal weddings, but also serious issues, including bias, false positives, and other potential life-changing errors. Police forces around the world have begun to use face recognition in nature despite studying the study that shows serious errors, and the authoritarian potential of technology has become painfully clear in China, where one of many tools used to suppress uighur -minoriteten.
All this is unpleasant to read, but as a result of these controversies, companies have begun to construct tools to combat bias problems, and large-technology companies that Microsoft is now open to regulate Face. To read this news in a positive light, more controversy means scrutiny, and – in the long run – more solutions.
And despite this cascade of scandals, 2018 also saw dozens, hundreds of hopeful and positive deployments of machine learning and AI. There were small victories everywhere from astronomy, where machine learning discovered new craters on the moon and overlooked exoplanets; to basic scientific research, such as using AI to develop stronger metals and plastics; and health care, where there have been many examples of AI systems capable of detecting diseases faster and more accurately than humans. New tools like plug-and-play machine learning services from Google and Amazon, and available learning programs from organizations like Fast.ai, have provided artificial intelligence to multiple hands, and the results have been largely beneficial and often inspirational.
These successes do not balance the bigger mistakes, but together they show that AI is a complex field. It doesn't move in a single moral direction, but like all technologies it has been taken up by a number of different players using it for a variety of outcomes.
Looking out over the year as a whole, a lesson stands out: AI is not magic. It is not a two-letter incantation that can be used to call venture capital and institutional confidence in a whim; It is also not fairy dust that can be sprinkled over products and institutions for immediate improvements. Artificial intelligence is a process : something to be examined, considered, and – if all goes well – understood. In other words, long accounts can continue.
Final grade: B
Verge 2018 report card: AI
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- AI Tools Get More Available
- Countless uses are found in a diverse range of fields
- A world-class technology that only begins to pace
Need for improvement surveillance and assistant authoritarian states