Totale Eigenständigkeit von Smart Machines ist vielleicht weder möglich noch wünschenswert

Bis zum Jahr 2020 werden Smart Machines eine der Top 5 Prioritäten sein, in die mehr als 30 Prozent der CIOs investieren werden, so das IT-Research und Beratungsunternehmen Gartner. Nachdem sich Smart Machines erstmalig dem autonomen Betrieb nähern, steht die Ausübung von Kontrolle dem vollen Nutzen der Vorteile von Smart Machines diametral gegenüber.


Gartner Says Full Autonomy May Not be Possible or Desirable in Smart Machines



GOLD COAST, Australia, 27 October, 2016 — By 2020, smart machines will be a top five investment priority for more than 30 per cent of CIOs, according to Gartner, Inc. 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.

Presenting Maverick research [1] findings at Gartner Symposium/ITxpo in Australia today, Brian Prentice, research vice president at Gartner, said Google’s self-driving car project is a perfect example of why pursuing full autonomy may be neither possible nor desirable in smart machines.

»Human beings are still required as the final point of redundancy in an autonomous vehicle, so a fully autonomous car requires a steering wheel should a driver be required to take control,« said Mr Prentice. »But putting a steering wheel in an autonomous car means a fully licensed, 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 potenzial failure.«

According to Gartner, the »Google Steering Wheel Dilemma« is representative of a challenge all smart machine initiatives must face.

»Smart machines respond to their environment. But what is the environment that the smart machine is responding to? Environments that are largely uncontrollable are not amenable to smart machine projects because it is difficult, if not impossible, to model accurately,« said Mr Prentice. »The trick then is to figure out what is actually controllable and limit smart machines to that which can be accurately modelled and managed.«

Mr Prentice said that 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.

»The vision of the fully autonomous vehicle will not become reality, for any car manufacturer, in a time frame that doesn’t fall into the realm of science fiction,« said Mr Prentice. »The failure of this vision will be set against the backdrop of advances in smaller, more pragmatic applications of machine learning in automobiles that will improve safety and driver experience.«


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.
  • At the beginning of any project aiming to make use of smart machine technologies, identify and analyse the constraints within the environment — in law and in public attitudes — that the eventual solution will face.
  • Design any smart machine solution outward from constraints identified in the key areas of user experience, information asymmetry and the business model to hit the sweet spot for smart machine-enabled solutions, and maximise the benefit the technology will provide.


[1] Gartner’s Maverick research is designed to spark new, unconventional insights. It is unconstrained by Gartner’s typical broad consensus-formation process to deliver breakthrough, innovative and disruptive ideas from the company’s research incubator to help organisations get ahead of the mainstream and take advantage of trends and insights that could impact IT strategy and the wider organisation.

Gartner clients can read more in the report: »Maverick* Research: Resolving the Google Steering Wheel Dilemma in Smart Machine Design.« This research is part of the Gartner Special Report »Maverick* Research«, a collection of research designed to spark new, unconventional insights.

About Gartner Symposium/ITxpo

Gartner Symposium/ITxpo is the world’s most important gathering of CIOs and senior IT leaders, uniting a global community of CIOs with the tools and strategies to help them lead the next generation of IT and achieve business outcomes. More than 23,000 CIOs, senior business and IT leaders worldwide will gather for the insights they need to ensure that their IT initiatives are key contributors to, and drivers of, their enterprise’s success.

Video replays of keynotes and sessions are available on Gartner Events on Demand. Follow news, photos and video coming from Gartner Symposium/ITxpo on Smarter With Gartner, on Twitter using #GartnerSYM, Facebook and LinkedIn.

The Gartner Symposium/ITxpo 2016 taking place in Europe will take place from 6-10 November in Barcelona, Spain.

4. Industrielle Revolution: Social Machines im Kontext vom M2M

Media Equation: Die »Vermenschlichung« von Computer und Smartphone

Die Top 10 der strategischen Technologie-Trends für 2017

Hype Cycle for Emerging Technologies 2016

Top 10 der strategischen Technologien für Behörden im Jahr 2016

Digital Business: Unternehmen brauchen eine Vision für ihre Branche

Die Top 10 Technologien für Hochschulbildung

Siri, Cortana & Co. – Nützlich oder Spielerei?

Wer dominiert den IT-Markt in 2025? Industriekonzerne gegen Internet-Giganten

Die Funktionalität von Neuronen in Phase-Change-Technologie erstmals imitiert

Schreiben Sie einen Kommentar