Autonomy Is Not Intelligence: Stepping Into The Golden Age of Robotics
For an eternity, experts have equated robot intelligence with autonomy. They were wrong.
For the world to move past the precipice and into the golden age of robotics itself, the robots of today will need to move from being autonomous to truly being intelligent.
What does this mean?
There are three steps that build upon the baseline of autonomy that we need to take.
The first thing we have to do feels a bit counterintuitive: we have to make robots more responsive. This feels a bit in conflict with the idea of autonomy, but in reality is actually quite complimentary. How so? While a good robot should go about its learned routine autonomously, it should also be perpetually ready to take instruction from its owner to meet a current need that its routine would not expect, or necessarily know immediately how to handle. Consumers expect that robots will deliver a personalized experience that seamlessly fit into to their lives. To do this, they need to listen and take direction.
We have to make robots more responsive. While a good robot should go about its learned routine autonomously, it should also be perpetually ready to take instruction.
Let’s think of an example specific to Roomba: Let’s say you’re the proud parent of a 6 month old baby (congratulations!). When baby eats, baby is in a highchair, and when he or she is in a highchair eating, you better believe a mess will appear on the floor beneath the chair. Once the mess is made … you don’t want to wait for Roomba to start its regularly scheduled routine to eventually clean under the highchair. You want to be able to ask Roomba to come clean under the highchair right away.
If Roomba encounters something on the floor with which it’s not entirely familiar – say a wet spill of an unknown liquid (go ahead and let your mind run wild) – wouldn’t it be better for Roomba to ask its owner what the owner would like Roomba to do before attempting to drive over and vacuum it?
This is what I mean when I talk about robots that are responsive, providing a personalized experience. To put it simply: they need to be able to take direction and ask for it when circumstances require. Beyond improving performance and outcomes, a robot that is responsive drives the relationship between robot and owner closer to one based on trust. And as someone who runs a company that has sold 25 million robots, I can assure you trust is not granted at the point of purchase. Trust is earned over time. It's why so many owners of Roombas watch them vacuum when they first bring them home. It must be proven to them that Roomba will do what it promises to do.
To put it simply: they need to be able to take direction and ask for it when circumstances require.
How else must robots evolve to be closer to intelligence?
A robot must be collaborative. To accomplish this we must broaden the awareness and understanding of the robot beyond its immediate environment to people and other robots as well. For example, if Roomba encounters some unknown liquid substance on the floor, perhaps it asks its owner for guidance… but also offers the option for a Braava robot to come mop up the wet spill instead. Should the owner of the robot provide guidance that Braava do the job, Roomba could then signal to Braava to come do the job, and provide it location information on the spill to be cleaned. Braava then comes and does the job, and Roomba goes out completing the rest of its mission. Collaboration complete. Over time, one could expect the robots to take the proper collaborative action without asking the owners for input as they learn what liquid spills they should and should not clean.
A robot must be collaborative. We must broaden the awareness and understanding of the robot beyond its immediate environment to people and other robots.
This collaborative dynamic also further evolves the relationship between robot and owner from one of trust to that of a trusted partnership. Why? Because a partner not only listens, a partner learns. Given enough inputs by the owner, a robot should be able to learn, and when the unusual circumstance crops up again in the future, take action without asking for input as the robot has learned what to do from past experience.
The third step is that robots must take towards true intelligence is to act as part of a larger system. Think of your house as a potential system. It has rooms, and we tend to go into rooms for a task and leave for something else. If your Roomba understood what devices are in what rooms, suddenly your house could operate more like a system, for example, allowing you start watching a TV show in one room, and have that show follow you into another room, which makes for an optimal experience for you. In addition, the room you were in previously would know to turn itself off – lights off, TV off - thus allowing you to save energy.
Robot must act as part of a larger system. Think of your house as a potential system.
There’s one more important dynamic that is critical – the most critical – to robots stepping into the golden age: people must trust them as partners. It’s why it’s so critical that robots deliver progressively on the three steps I listed above. By delivering on these steps robots will engender the kind of the trust that is at the foundation of a true partnership. With trust granted by people and partnership achieved through that trust then and only then can robots be given permission by people to empower people to do more.
People must trust robots as partners. Only then can robots be given permission by people to empower people to do more.
At iRobot, we’re not just talking about these steps, we’re taking them. You can already ask your Roomba robots to clean a specific room in your house on demand via voice command to Amazon or Google smart speakers or via the iRobot HOME app. We call it Directed Room Cleaning and it’s our robots’ most popular digital feature – even more so than scheduling! Roomba and Braava can already collaborate together to clean an entire floor of the house or a specific room depending on your preference through Imprint Link technology. With respect to building a system for the home – the smart home – Roomba already holds the keys to the proper foundation for one: spatial understanding.
The movies promise that autonomy is the answer, but it is a false promise. The golden age of robotics won’t dawn until robots truly understand your home, can listen and take direction. Once this is accomplished, a world of possibilities exist. Robots talking to Robots. Robots providing intelligence and instructing other devices in your home. There’s much more to come on that front, but for now I’ll just ask this: if I told you the smart home of tomorrow is actually a robot… would you believe me?
Stay tuned because I’ll explain why in a future blog post. Until then, let me know what you think it's going to take for us to step into the Golden Age of Robotics - comment below!
I periodically post blogs on LinkedIn, but tweet regularly on Twitter - follow me @ColinAngle if you don't already.
CEO @ Perrone Robotics || Host @ DRIVEN podcast (AI, Robotics, AVs)
4 年Thank you for posting. It makes perfect sense. I would also add that I think, at least in the autonomous vehicle space (with some application to other mobile robotics spaces), that deep learning is currently over-stressed as the solution for autonomy. It sometimes strikes me that deep learning is stressed by some because it is an intellectually interesting topic, or perhaps something that garners investment capital, versus something commercially driven. I tend to think determinism and control are more important for safe and practical robotics to flourish. I’d liken it to the Wright Brothers who’s approach of control and stability for commercial flight was the winning ticket for aerospace to flourish over the more bio-inspired flapping winged flight approaches that were attempted and ultimately didn’t work out. By analogy, control-first with robotics and rule-based expert systems, while less “new” than certain deep learning approaches, allows for more determinism than the probabilistic (e.g. neural network based) approaches to autonomous vehicle development….where unexpected and unanticipated events carry with them a high severity. And as the complexity of the system grows, the complexity and lack of verifiability of these systems becomes impossible. Deep learning has a role and can augment a system, but the deep learning and strong AI focus of some autonomous vehicle approaches seems like an impending train wreck and a potential setback for the Golden Age of Robotics.
Engineering Consultant - Robotics, Embedded Systems, Software
4 年My two year old son is autonomous. Doesn't mean I want him to run a manufacturing line.
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4 年If you think about it with an open mind, humans are an advanced species of robot and we are in process of reinventing ourselves as humanoids, which will become reality when biogenetic science converges with quantum digital technology. As that occurs and we have the ability to download and upload intelligence to, from and between brain/minds. As such, we will create a genuine human digital twin that will have all the capabilities, including thought and emotions, of humans, with very advanced intelligence. AI is not Artificial but very real and soon will become Advanced. That will be the golden age of what I call a BioDigiTransHuman Species.
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4 年This seems similar to what we wrote about on this same concept: https://www.forbes.com/sites/cognitiveworld/2019/11/14/automation-is-not-intelligence/#3005e73f61d6
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4 年Great post Colin! Looking forward to the "Golden Age."