Originally posted on The Horizons Tracker.
AI and robotics has progressed at a tremendous rate in the past few years, and this progression has led to a number of doom-laden proclamations about its potential impact on jobs, with academics and government lending their voice to the potential downside to AI.
There has also been a response from industry, with the Partnership on AI created by a cohort of tech companies, including IBM, Microsoft and DeepMind. The group was created to“study and formulate best practices on AI technologies, to advance the public’s understanding of AI, and to serve as an open platform for discussion and engagement about AI and its influences on people and society.”
Of course, it’s certainly not uncommon for the media to dwell on the risks of any new technology, and there are certainly a wide range of exciting possible use cases for AI in the coming years. A recent report from Data Innovation set out to showcase a number of them.
The promise of AI
The report attempts to stay as grounded as possibly by focusing its 70 examples of AI in practice very much in the realm of soft-AI rather than hard-AI. This is the kind of AI that can perform very well in a relatively narrow range of tasks, but isn’t capable of learning on the fly or any of the more expansive tasks currently being researched around the world.
So it’s fair to say that the report keeps it’s feet firmly on the ground of what is possible now rather than what might be possible in future. It breaks the 70 examples of AI into 14 categories:
- accessibility, including support for those with visual and hearing impairments
- agriculture, including vertical farming and crop monitoring
- business operations, including customer service and office assistants
- consumer convenience, including financial advise and household support
- disaster prevention and response, including detecting disease outbreak and earthquake prediction
- education, such as teaching support and language tuition
- energy, such as modelling energy consumption and increasing data efficiency
- environment, whether stopping the spread of deforestation or supporting anti-poaching efforts
- health care: prevention and screening, such as diagnosing speech disorders and screening for disease
- health care: treatment and monitoring, including streamlining drug development and robotic surgery
- industrial operations, such as early fault detection and factory automation
- public safety, including crime predictions and bomb disposal
- social good, whether in predicting poverty or tackling human trafficking
- transportation, with a panoply of self-driving technologies under development
The authors openly admit that these are but a few of the huge range of use cases for automation and AI today, but if you’re still relatively new to the topic then it provides a good overview of the fields being worked on, many of which have been covered on this blog over the past year or so.
Which do you think will have the biggest impact?
Article source: 70 use cases for AI today.