Fourth Industrial Revolution

Can machines think? A new Turing Test may have the answer

Social humanoid robot Sophia, a latest creation by Hanson Robotics company, attends a news conference after a meeting with young inventors and officials in Kiev, Ukraine October 11, 2018.  REUTERS/Valentyn Ogirenko     TPX IMAGES OF THE DAY - RC19B71A1060

How close to perfection are we? Image: REUTERS/Valentyn Ogirenko

Carl Strathearn
PhD Candidate, , Staffordshire University
Share:
Our Impact
What's the World Economic Forum doing to accelerate action on Fourth Industrial Revolution?
The Big Picture
Explore and monitor how Fourth Industrial Revolution is affecting economies, industries and global issues
A hand holding a looking glass by a lake
Crowdsource Innovation
Get involved with our crowdsourced digital platform to deliver impact at scale
Stay up to date:

Emerging Technologies

Alan Turing was recently announced as the face of the new £50 note for his code breaking contributions in World War II and laying the foundations of computer science. However, Turing’s work still challenges and inspires many people working today, especially those in robotics and artificial intelligence.

In 1950 he asked, “Can machines think?”, and came up with a test that researchers still turn to as a way of judging whether a computer could be considered truly intelligent in the same way as humans. But, coming from an age where autonomous robots were only just in their infancy, the Turing Test was only designed to assess artificial brains, not a complete artificial person.

Now that we have increasingly realistic looking androids, we need a 21st-century version of the test. My colleagues and I have designed a “Multimodal Turing Test” to judge a machine’s appearance, movement, voice and what we call embodied artificial intelligence (EAI). This is a measure of how well artificial intelligence is integrated with a robotic body in order to expresses a personality.

This means we can systematically compare a humanoid robot to a living counterpart. In this way, we can ask the question: “Can we build robots that are perceptually indistinguishable from humans?”

Not there just yet.
Not there just yet. Image: Carl Strathearn,Author provided

Turing argued that if a computer program could deceive more than 30% of humans into believing it was sentient in real-world conditions, then it is effectively indistinguishable from the human mind – it can think. A computer was able to pass this test in 2014. That doesn’t mean there’s no work to do to create true artificial intelligence. Far from it. But the Turing Test gives us a benchmark to judge our progress.

Many scholars think creating a humanoid robot that is indistinguishable from a real human is the ultimate goal of robotics. Yet there’s currently no standard way of evaluating how lifelike androids are, so it’s impossible to benchmark this development.

Like Turing, we’re not arguing that a robot transforms into an organic being when it can replicate the conditions of a human. But if a robot appears, behaves and functions in a way that is indistinguishable from a human being in real-world conditions, then it can effectively be thought of as the same as a human.

One of the biggest challenges for lifelike robot builders is overcoming what’s known as the “uncanny valley”. This refers to a stage of development when robots become closer in appearance to humans but are actually more offputting to people because they are not quite right. The issue is that conventional methods of assessing the problem aren’t nuanced enough to determine exactly why a robot makes people uncomfortable.

The test breaks down the robot building process.
The test breaks down the robot building process. Image: Carl Strathearn,Author provided

These approaches tend to compare the robot as a whole with a human, rather than breaking it down into its component features. For example, a slight miscalculation in the movement of the eye of an otherwise realistic looking robot can give the whole game away. High quality features of other facial areas then become part of that failure.

Our idea is to evaluate each area step by step. As long as each feature is designed to look like it is part of the same body (same gender, age and so on), then if an eye and mouth can individually pass the test then they should also pass it together. This would allow a robot builder to assess progress as they go to ensure each body part is indistinguishable from a that of human and to prevent ending up with something that falls into the uncanny valley.

Have you read?

Our test is also organised into four stages, each more difficult than the last, representing what we call the “hierarchy of human emulation”. First, the robot has to simply look real when still. Second, it has to move in a naturally looking way. Third, it has to produce a realistic simulation of physical speech in both appearance and the way it moves.

Finally comes the test of embodied artificial intelligence, assessing whether the robot can respond to the world by realistically expressing emotions so it can interact naturally with humans. If a humanoid robot can simultaneously pass all four levels of the test, then it is perceptually indistinguishable from humans.

Passing for human?
Passing for human? Image: Carl Strathearn,Author provided

“We can only see a short distance ahead, but we can see plenty there that needs to be done”. This statement is as accurate today as the day Turing said it in 1950. However, robotic engineers are closer than ever before to achieving their goal of a realistic humanlike machine, and 2017 witnessed the inauguration of the world’s first robotic citizen.

Today, we have the tools to develop humanoid robots with increasingly lifelike appearance, movement, speech and EAI. But our Multimodal Turing Test gives engineers an accessible way to evaluate and so improve their work.

As with Turing’s original test, our approach raises questions about what it will mean to be a person when we can no longer tell the difference between a real human and an artificial one. Trying to answer these questions too soon because we want to advance quicker than we actually are can lead to mistakes such as giving legal rights to a machine that is nowhere near lifelike. But the more we develop humanoid robots, the more we learn about our values and even our emotions.

Don't miss any update on this topic

Create a free account and access your personalized content collection with our latest publications and analyses.

Sign up for free

License and Republishing

World Economic Forum articles may be republished in accordance with the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International Public License, and in accordance with our Terms of Use.

The views expressed in this article are those of the author alone and not the World Economic Forum.

Related topics:
Fourth Industrial RevolutionEmerging Technologies
Share:
World Economic Forum logo
Global Agenda

The Agenda Weekly

A weekly update of the most important issues driving the global agenda

Subscribe today

You can unsubscribe at any time using the link in our emails. For more details, review our privacy policy.

Generative AI is rapidly evolving: How governments can keep pace

Karla Yee Amezaga, Rafi Lazerson and Manal Siddiqui

October 11, 2024

About us

Engage with us

  • Sign in
  • Partner with us
  • Become a member
  • Sign up for our press releases
  • Subscribe to our newsletters
  • Contact us

Quick links

Language editions

Privacy Policy & Terms of Service

Sitemap

© 2024 World Economic Forum