As for many tech companies, 2018 is a year of artificial intelligence. As AI systems have been integrated into more products and services, the shortcomings of technology have become more apparent. Researchers, businesses, and the general public have begun to grapple with the limitations of AI and and its detrimental implications, asking important questions such as: how is this technology used, and to what extent?
This bill was most clearly visible as a parade of negative headlines about algorithmic systems. This year, the first deaths were caused by self-driving cars. the Cambridge Analytica scandal; Allegations that Facebook has favored the genocide in Myanmar; the revelation that Google helped the Pentagon train drone surveillance tools; and ethical questions about the tech-savvy human-sounding AI assistant. AI research group described 201
However, these headlines do not have to be considered but only as negative. After all, a scandal is better than an evil that goes unnoticed, and controversy can theoretically help us improve.
Face recognition. This was one of the fastest moving technologies in 2018, with successes such as For example, investigations by the Chinese police at a music concert held by a criminal and broadcasting company that use guests to identify guests at the royal wedding, but also serious issues, including bias, false positives. and other potentially life-changing mistakes. Police around the world have begun to use facial recognition in the wild, though study found serious shortcomings after the study, and the authoritative potential of the technology has become painfully clear in China, where it is one of the many tools to suppress the Uighur minority.
All of this is uncomfortable to read, but as a result of these controversies, companies have begun to develop tools to tackle problems of bias, and large tech companies like Microsoft are calling now open regulation face recognition. To read these messages in a positive light, more controversy means a review and more solutions in the long run.
And despite this cascade of scandals, 2018 saw dozens, hundreds of hopeful and positive uses of machine learning and AI. Everywhere in astronomy there were small profits, where machine learning discovered new craters on the moon and overlooked exoplanets; for basic scientific research, eg B. AI for the development of stronger metals and plastics; and healthcare, where there are many examples of AI systems that can detect diseases faster and more accurately than humans. New tools such as Google and Amazon machine-learning plug-and-play services, as well as accessible learning courses from organizations such as Fast.ai, have given artificial intelligence more hands-on, and the results have been of great use and often inspiring.
These achievements do not compensate for the larger failures, but taken together they show that AI is a complex field. It does not move in a single moral direction but, like all technologies, has been picked up by a variety of actors who use it for a range of outcomes.
If you look at it throughout the year, one lesson turns up: AI is not magic. It is not a two-letter incantation that can be used to summon venture capital and institutional trust on a whim. It is also not fairy dust that can be scattered for immediate improvement via products and institutions. Artificial intelligence is a process : something to investigate, to think about and – when all is understood. In other words, billing can take a long time.
The Verge 2018 Report Card: AI
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- AI tools are becoming increasingly accessible
- Countless use cases in various fields
- A world-changing technology that is slowly becoming prevalent
Potential for increased surveillance and support of authoritarian states