Full autonomy may not be possible or desirable in smart machines and human beings are still required as the final point of redundancy in an autonomous vehicle, a new report by market research firm Gartner said on Friday. “Major unresolved problems in machine-learning solutions, such as how to ensure learning data is fully representative and how to avoid reward hacking, need to be addressed before any autonomous machine that continues to learn from its environment can be deployed as a mass-market solution to a real-world problem,” said Brian Prentice, Research Vice President at Gartner, in a statement.
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With smart machines moving towards fully autonomous operation for the first time, balancing the need to exercise control versus the drive to realise benefits is crucial.
Google’s self-driving car project is a perfect example of why pursuing full autonomy may be neither possible nor desirable in smart machines, Prentice pointed out.
A fully autonomous car requires a steering wheel should a driver be required to take control. But putting a steering wheel in an autonomous car means a fully licenced, sober driver must always be in the car and prepared to take control if necessary.
Not only does this destroy many of the stated benefits of autonomous vehicles, but it changes the role of the driver from actively controlling the car to passively monitoring it for potential failure.
“The vision of the fully autonomous vehicle will not become reality, for any car manufacturer, in a time frame that does not fall into the realm of science fiction,” Prentice noted.
By 2020, smart machines will be a top five investment priority for more than 30 per cent of CIOs, the report noted.
According to Gartner, CIOs seeking to maximise the benefits of smart machine solutions must plan to deliver smart machine-enabled services that assist and are overseen by humans to achieve maximum benefit in the next three to five years, rather than those that are fully autonomous.
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