Artificial Intelligence and Machine Learning
Artificial Intelligence and Machine Learning (3:32)
“The difference between artificial intelligence and robotics is that artificial intelligence is software, how can your robot think, whereas, I think, robotics is much more of the system level, as we would say, which is not just how is it thinking, but how is it moving? How is it interacting? How can it see what’s going on around it? And so robotics encompasses artificial intelligence and utilizes a lot of artificial intelligence.”
Role models in order of appearance: Taniya Mishra, Randi Williams, Betelhem Dessie, Mia Stevens, Ehi Nosakhare, Ifueko Igbinedion, Amy Hemmeter, and Steffi Paepcke.
1) One role model explained that algorithms are “a way to make computers do things that humans think are intelligent.” What types of things do humans think are intelligent? Why might we want computers to do these things?
2) Listeners learned that algorithms can be biased. How might algorithms become biased? Why would this be bad? What can we do to help prevent biases from entering our algorithms?
3) In the video, some of the role models work in machine learning. What is machine learning? What types of tasks can be accomplished through machine learning? Is this a career that might be interesting to you? Explain your answer.
4) Many of the role models spoke about the ability of robotics and artificial intelligence to help older people or disabled populations. How can artificial intelligence help these groups of people? What might be some challenges of introducing this technology to older or disabled people? How might those challenges be overcome?
5) The role models discussed self-driving cars and robots as examples of ways that this technology could help elderly people. What other future uses of artificial intelligence, machine learning, or robotics can you think of? Who would benefit from each of the uses you thought of? Can you think of any drawbacks related to the use of artificial intelligence, machine learning, or robotics?
6) Listeners heard the role models use lots of mathematical language such as modeling, algorithm, and scenario. Do you think you have to be a math genius to work in these fields? Why or why not? If you are interested in a career in one of these fields, how could you begin preparing now?
Artificial intelligence is algorithms that mimic human intelligence. And algorithms are simply a set of rules, a recipe, so to speak, of how do you behave like a human being.
It’s a way to make computers do things that humans think are intelligent. So this could be, yeah, solving math problems, maybe even navigating around, but also giving directions, making art, speaking. These are all things that, when you see humans do it, you’re like, “Oh, this is a sign of intelligence.” And so now we’re making computers do those kinds of things.
So algorithms are very important because computers cannot decide by their own. Algorithms are a way for them to decide what to do next or what they should do. So it’s very important that when a person decides an algorithm, that you think of every possible case scenario that you would put in. And that’s one of the reasons that it’s very important, especially when you come to the development of AI and robotics.
The difference between artificial intelligence and robotics is that artificial intelligence is software, how can your robot think, whereas, I think, robotics is much more of the system level, as we would say, which is not just how is it thinking, but how is it moving? How is it interacting? How can it see what’s going on around it? And so robotics encompasses artificial intelligence and utilizes a lot of artificial intelligence.
Machine learning, which is a subset of artificial intelligence, pretty much is thinking through building the mathematical modeling that makes these tasks possible. The reason why we do this is because computers are very good at doing math very fast, and they’re also very good at doing repetitive tasks.
Humans can really benefit from artificial intelligence when difficult tasks that often cost a lot of money to do or multiple people to solve become possible when we have artificial intelligence.
Machine learning in healthcare is actually really growing. One area is in the area of computer vision. We are starting to see algorithms that are doing better and better at diagnosing things like cancer, for example.
Self-driving cars are going to change the world drastically for people with disabilities. People who are blind or legally blind, people who can’t drive for whatever reason are going to be more independent, and it’s going to change their lives hugely in a positive way.
In Japan, where they were having this older adult population that was getting huge, and then there weren’t as many people who were able to take care of them. And so the goal of the project was to build robots that could help support the older adults and help them be more independent.
As people get older, sometimes their reach kind of shrinks a little bit, and maybe they stay closer to their home. But I think with new technologies, we can help people really reach out further and travel further distances and reach people who are further away, and I think that’s a really exciting opportunity.
There are ethical considerations when thinking about AI, in that are algorithms really fairly representing the population that we have? And are these algorithms smart enough to take over? And things like that. But I think, rather than being afraid of, “What are the possibilities that could happen negatively?” why can’t we just all work towards it, understand it, and make sure that the future of the field is one that is ethical and positive?
Independent Learning Guide: This all-purpose guide can be used by educators, parents, and mentors to jumpstart a lively discussion about careers in Artificial Intelligence and Machine Learning.
AI, Machine Learning and Robotics is an important and growing field. Challenge yourself to learn just one of these AI, Machine Learning and Robotics terms each day.
Classroom Lesson Plan: This step-by-step lesson plan is available to guide a more in-depth “before, during, and after” learning experience when viewing the video with students. This lesson plan is also suitable for use in after-school programs and other educational settings.
Use Empowerment Activities as a fun way to reinforce the video topic and build community with your students.
Related Empowerment Activities:
Fun Page Activity: Scientists and engineers use algorithms to teach computers how to do things. But did you know that we all use algorithms every day? Learn about algorithms and create your own in this fun page activity!