Conclusions and Reflections

We have been on quite a journey throughout this book. I’ve learned a lot, and I hope you have as well. I've had the chance to revisit my love of robotics and spend a lot of time examining the state of the art of artificial intelligence (AI) and robot design to try and find a way to explain the concepts to you in an easily digestible form.

In this chapter, we will discuss finishing our robot. I’ll provide you with some advice on careers in AI and robotics. We will also talk a little about the future of AI, at least as I see it, and finish with a discussion about risk.

The following main topics will be covered in this chapter:

• Learning when to stop
• Careers in robotics
• Exploring the current state of AI
• Understanding risk in AI

Learning when to stop

Over the last nine chapters, we’ve worked on designing a specific robot to perform a specific task. We designed Albert the robot to pick up toys in an unstructured environment, namely a family home. To do this, it needed to be able to recognize toys with a camera, pick up toys with a robot arm and hand, navigate inside a house, and deposit toys in a toy box. We also added interaction, teaching the robot to listen and react to commands. Finally, it received an artificial personality and simulated emotions.

So, the next question is, are we finished with designing, building, and testing our robot? Sometimes, the most difficult part of designing, building, and testing a robot is determining when it is finished. Quite often, I see that some little thing might be improved, or some detail added, or some feature enhanced. Oh, the robot needs a spotlight. It would be nice if it could remember what toys are in the toy box. What if it had two arms? And so on. You...

Careers in robotics

I am often asked what sorts of skills or degrees robot designers need to have, or what courses they should take. I meet a lot of young people at robot competitions, student events, conferences, and recruiting trips. A lot of the advice I give people I have put into this book already – especially now that AI, neural networks, graphics processing units (GPUs), expert systems, chatbots, navigation, and image processing are all important. You need to understand that robotics is an umbrella term that covers a lot of industries and a lot of skill sets.

Who uses robotics? The range of applications is continuing to grow every day. These include the following:

• In the medical field, there is robot-assisted surgery, robotic prosthetic limbs, exoskeletons helping paraplegics to walk, and implantable devices to help people hear and see.
• We have self-driving cars and self-flying airplanes and helicopters in transportation (which is what I do).
• We have...

Exploring the current state of AI

There is a lot of hype going on right now in the intersecting worlds of AI and robotics. And a lot of it is just exaggeration.

One common myth is that robots are taking jobs away from people. In truth, robots and automation free up workers to do more productive tasks. The truth of this can be seen in job statistics – unemployment in the US is at a 50-year low (https://www.wsj.com/articles/january-jobs-report-unemployment-rate-economy-growth-2023-11675374490), despite massive improvements in factory automation. However, according to The Harvard Business Review, the improved productivity of robotics creates more jobs than it removes (https://hbr.org/2021/03/why-robots-wont-steal-your-job). The overall level of employment has increased, not gone down because of automation and increased productivity.

I do recognize that the modern worker, even someone like myself, who works in technology, must be ready and willing – at any age –...

Understanding risk in AI

One subject I talk about frequently at conferences and in print is the risk of AI in terms of trust and control. I’m not talking about AI running amok here, but rather how to make AI dependable. It is quite interesting that the sort of AI we have been considering – specifically, ANNs – does something very few other computer software do. Given the same inputs and conditions, the output of an AI system is not always the same. Given the same inputs, the AI system will sometimes come up with a different answer. The formal name for this behavior is non-determinism.

There is a second corollary to this. Given the same inputs, the AI process will sometimes take a different amount of time to complete its task. This is simply not normal behavior for a computer.

Admittedly, we are not using AI to get answers to math questions such as 2+2, but rather how to do things such as diagnose a cancer tumor or recognize a pedestrian in a crosswalk for...

Summary

In this final chapter of this book, we summarized our journey through robotics and AI. We talked about robotics as a career and discussed AI robotics as a profession. I brought up some issues regarding the future of AI, both real and imaginary. Drones and self-driving cars are real; robots taking jobs from humans or taking over the world is imaginary, at least in my opinion. I talked about robots and AI not having needs, and thus lacking the motivation, pressure, or even capability to evolve. Finally, we talked about risk in AI and how to recognize it. I hope that this information gives you some guidance in your interest in robotics and AI and provides some insider information from a practitioner in this area.

Now that we’re almost at the end of this book, I want to thank you for coming on this journey with me. I hope you have learned something along the way, even if it is just to know more questions to ask. I encourage you to dive in and build your own robot, learn...

Questions

1. Given that we started the chapter on a light note and ended up talking about robot phobia and philosophical questions about existence, do you feel that AI is a threat? Why or why not?
2. List five professions that would be necessary to turn our Albert robot into a product company.
3. If we imagine a company that was going to put Albert the robot into production, would it need a psychologist? For the robot, or for the humans?
4. What components found in cell phones or smartphones are also found in quadcopters?
5. Why are AI systems, specifically ANNs, naturally non-deterministic in terms of results and time?
6. What might be a practical application of an AI system that predictably makes mistakes?
7. If an AI system was picking stocks for you and predicted a winning stock 43% of the time, and then you had a second AI that was 80% accurate at determining when the first AI had not picked a good stock, what percent of the time would the AI combination pick a profitable...

Further reading

• The Organization of Behavior, by Donald Hebb, Wiley.
• Computing Machinery and Intelligence, by Alan M. Turing in the journal Mind. Vol. LIX (238).
• Feet of Clay, by Terry Pratchett, published by HarperCollins, London 2009. This book discusses the fictional concept of golems, which are clay creatures that are programmed by a set of instructions written on paper and put into their heads, an interesting analog to robots.
• A Theory of Human Motivation, by A.H. Maslow in the journal Psychological Review, vol. 50 (4).
• US Dept. of Transportation. National Motor Vehicle Crash Causation Survey. https://crashstats.nhtsa.dot.gov/Api/Public/ViewPublication/811059.
• Attacking Faulty Reasoning: A Practical Guide to Fallacy- Free Arguments, by T. Edward Damer, Cengage Learning.
• Modern Generative AI with ChatGPT and OpenAI Models, by Valentina Alito, Packt Publishing.