The Spelman College SpelBots: Remembering Black Women AI and Robotics Pioneers at 20 Years

Think about what strides we’ve made in artificial intelligence in the last 20 years. Driverless cars, ChatGPT, Siri, Deep Learning, and the list goes on. One little-known fact is that a group of Spelman College black women were doing things with artificial intelligence 20 years ago that, even today, only a small fraction of people could do or even think of doing. How do you program four-legged and two-legged humanoid robots to autonomously play soccer using computer vision, machine learning, and localization without the robot being remote controlled? How do you combine AI and robotics with the arts and healthcare to inspire the next generation of computer scientists and engineers around the country?

With the support of the Spelman president, Beverly Daniel Tatum, our science dean, Dr. Lily McNair, Spelman alumni and board members, and our sponsors such as the National Science Foundation, NASA, Coca Cola, Boeing, GM, GE, Apple and Google, the Spelman SpelBots traveled the world to compete in autonomous quadruped and humanoid soccer in Japan, Germany, Italy, and the U.S against some of the leading universities in the world that were doing research in AI and robotics two decades ago.

It was around March of 2004, when I went to Spelman College to interview for a position as an assistant professor in computer and information sciences. I was already an assistant professor at the University of Iowa in electrical and computer engineering but had read the book, The Purpose Driven Life, with my wife and decided that part of my God-given purpose was to help African American students succeed academically, vocationally and spiritually. As I shared in my book, Out of the Box: Building Robots, Transforming Lives, I interviewed at Spelman, Howard University, and had an informal interview at Morehouse.

When Spelman made me an offer, I wasn’t sure what I should do. But my wife said to me, “Andrew, don’t you want our daughters to have professors that really want to see them succeed.” And I decided to go even though many didn’t understand why I would leave a Big 10 research university for a small, historically black undergraduate liberal arts college for women. I would go there and see unlimited possibilities for my students and treat them as I would want a professor to treat and believe in my own daughters.

There are many stories I can tell about our experiences. My book just touches on the first team. When it was released I was working at Apple while on sabbatical from Spelman at the behest of the co-founder of Apple, Steve Jobs. He wanted me to help them hire more black engineers and I was able to do that. More importantly, these young women were pioneering AI and robotics role models, along with my colleague, Dr. Ayanna Howard, who mentored one of our first SpelBots students, Aryen, before the team was formed at NASA’s Jet Propulsion Lab. Aryen contacted me while I was moving to Spelman and I asked her if she wanted to start a RoboCup robotics team. She volunteered to be our first co-captain, along with a student named Brandy.

The AI and robotics topics that the undergraduate Spelman students had to grapple with to compete with graduate students at Georgia Tech, Carnegie Mellon, University of Texas Austin, and other international teams were daunting. The AI and robotics topics they worked on included localization, computer vision, motion, locomotion, teamwork, and decision making. I purposely made sure that I didn’t put limits on them and believed in them. There were several teams of SpelBots who did amazing things. Like the team that tied in a RoboCup Japan Open autonomous humanoid robotics championship match with Japan’s Fukuoka Institute of Technology’s team led by co-captains Jonecia and Jazmine. (There are so many more SpelBots students I can name here.)

So here’s to remembering the women of the Spelman College SpelBots RoboCup robotics team that competed in the U.S., Europe and Asia. Watch this video made by the National Science Foundation, and remember to help all of our young women dream big and pioneer in Science, Technology, Engineering, and Math (STEM).

Picture: Spelman College SpelBots students Jonecia, Jazmine, Ariel, Naquasha, and Dr. Andrew B. Williams at RoboCup 2009 Japan Open in Osaka, Japan Photo credit © Adrianna Williams, used with permission

© 2024 Andrew B. Williams

About the Author: Andrew B. Williams is Dean of Engineering and Louis S. LeTellier Chair for The Citadel School of Engineering. He was recently named on of Business Insider’s Cloudverse 100 and humbly holds the designation of AWS Education Champion. He sits on the AWS Machine Learning Advisory Board and is a certified AWS Cloud Practitioner. He is proud to have recently received a Generative AI for Large Language Models certification from DeepLearning.AI and AWS.  Andrew has also held positions at Spelman College, University of Kansas, University of Iowa, Marquette University, Apple, GE, and Allied Signal Aerospace Company.  He is author of the book, Out of the Box: Building Robots, Transforming Lives.

AI Autonomy Innovation: Teaching Cars to Drive by Themselves

Beneficial AI

Often, we hear about the negative aspects of AI but less about the potential benefits. At The Citadel, our cadets displayed their talents in using deep reinforcement learning algorithms to have cars drive by themselves. In the near future, think of how beneficial to have cars that can autonomously transport persons with disabilities such as blindness or limb dysfunction or the elderly who can no longer drive by themselves. How about having driverless supply vehicles that drive by themselves in a military environment?

Thanks to the support of Amazon Web Services (AWS), we were able to host the first 2023 Senior Military College and Service Academy Warrior Week DeepRacer Tournament. Cadets from The Citadel, the U.S. Military Academy at Westpoint, and the U.S. Naval Academy at Annapolis trained AI models to drive AWS DeepRacer cars all by themselves, or autonomously. DeepRacer is the name of the model car that has a video camera sensor to “see the road” and train an algorithm that can cause the car to drive by itself. The students train the cars virtually on a cloud-based simulator and then download the AI models to the DeepRacer car, which is used to drive the car on a real, or physical, race track. The algorithm they used was deep reinforcement learning.

Citdel Cadets Brian Bradrick and Blakely Odom, Dr. Pooya Niksiar (Coach) and the AWS Team Venkartaraja, Anthony Yimsiriwattana, Abhijeet Patil, Alex Domijan, and Nicholas Costas (not Pictured Cadet Frederick Vogel). Combined Heat Score showing Citadel Teams winning times followed by Cadet Teams from U.S. Military Academy and U.S. Naval Academy

AWS DeepRacer as an AI Autonomy Innovation Teaching Tool

Using DeepRacer as an AI teaching tool, is part of the autonomy innovation that our Center for AI, Algorithmic Integrity, and Autonomy Innovation, or AI3, hopes to bring to our students, community, and state. We hope that we can attract partnerships with major automotive companies in South Carolina, such as Volvo, BMW, and Mercedes to hire our students as interns and full-time engineers. We have also be partnering with AWS Machine Learning University’s AI Educator Enablement Program to put our faculty, include Dr. Pooya Niksiar, coach of our winning DeepRacer team, through Advanced AI and Machine Learning boot camps. This will prepare our faculty, and faculty across the U.S. at community colleges, HBCUs, and minority-serving institutions to teach machine learning at their institutions.

Drs. John Sanders, Nathan Washuta, and Gafar Elamin among the faculty and students in the DeepRacer Tourney audience speaking to team member Cadet Blakely Odom

The Winning Team – The Citadel School of Engineering

Finally, I want to give a shoutout to Dr. Niksiar and his team of three cadets, Frederick Vogel, Electrical and Computer Engineering, Blakely Odom, Mechanical Engineering, and Brian Bradrick, Mechanical Engineering, for taking First Place and Second Place against their competitors. We thank the U.S. Military Academy and the U.S. Naval Academy for their strong competition. We are happy that The Citadel School of Engineering can provide a world-class engineering education here in the low country and the State of South Carolina to serve our state and globe with principled leadership and engineering innovation.

AWS Pit Crew Member Anthony Yimsiriwattana Watching Citadel DeepRacer car navigate the track autonomously

Main Header Picture: Dean Andrew B. Williams, Dr. Pooya Niksiar (Coach), and Cadets Frederick Vogel (ECE), Blakely Odom (MECH), and Brian Bradrick (MECH), The Champions of the Inaugural Senior Military College and Service Academy Warrior Week DeepRacer Tournament

About the Author: Andrew B. Williams is Dean of Engineering and Louis S. LeTellier Chair for The Citadel School of Engineering. He was recently named on of Business Insider’s Cloudverse 100 and humbly holds the designation of AWS Education Champion. He sits on the AWS Machine Learning Advisory Board and is a certified AWS Cloud Practitioner. He is proud to have recently received a Generative AI for Large Language Models certification from DeepLearning.AI and AWS.  Andrew has also held positions at Spelman College, University of Kansas, University of Iowa, Marquette University, Apple, GE, and Allied Signal Aerospace Company.  He is author of the book, Out of the Box: Building Robots, Transforming Lives.

Draw to Lead: Visual Thinking and Communication in Innovation

“Let whoever may have attained to so much as to have the power of drawing know that he holds a great treasure.” — Michelangelo (not the Teenage Mutant Ninja Turtle one)

Today we had fun in our KEEN School of Engineering Book Club discussing and drawing (literally) from the book, “Draw to Win: A Crash Course on How to Lead, Sell, and Innovate with Your Visual Mind”, by Dan Roam. Our KEEN Book Club this semester is focused on visual thinking and communication. Why? To be innovative and to teach our students to be innovative, we need to tap into all that our brain has to offer to be creative and solve problems. Drawing allows us to connect ideas and create and communicate value, things vital to having an entrepreneurial mindset. And much of what the brain offers us in our innate creative conceptualization abilities through drawing, we often underutilize and fail to reach our ability to fully think and communicate in visual terms. According to the book, 90% of the information on the internet is visual, 90% of the data that ever existed was created in the last 2 years, and 90% of knowledge workers don’t know how to effectively use visuals.

Don’t Be Scared to Draw

In our book club, we talked about as kids, we used to draw all the time or have kids who are keen on being extra observant and engaged with illustrations and images. But somehow when we get older, we compare our scribbles and doodles with others and think, we don’t have the “gift”. But through Dan’s books, I’ve been discovering personally the power of using stick figures to not only communicate big ideas, but to allow them to form before my very eyes. I’ve made two presentations to big groups of professors (one on AI and another on mentoring) using stick figure drawings inspired by Dan’s book. I received comments and encouragement that they were drawn into (no pun into) the talk because the ideas were simple, clear, and uniquely presented.

What Makes a Good Drawing

As Dan says, good images are meaningful pictures that:

• trigger deep thoughts,
• clarify complexity, and
• inspire insight.

For the last few years, I have attended meetings, listened to sermons, and journaled with handwritten text and images. Not only does it allow me to work through thoughts in my head or create designs, it allows me to engage and retain information better and longer. Dan talks about how we often “draw” in our minds and bodies without a pen and pencil. You’ll have to get the book to learn more about that.

Drawing in the Classroom

One of our faculty in our club, Dr. Gafar Elamin, pointed out that for his mechanical engineering senior design class, he has the students sketch five different sketches that show the concept of their potential design. Soon the five sketches turn into twenty sketches, as they inspire new ideas and connections. Another faculty, Dr. Deirdre Ragan, said her honors students were making a presentation and apologized that their drawings weren’t that good. But when she told them, “artisticness” (my own choice of made-up word), isn’t what mattered. It was the ability of the drawing to communicate the idea. After that, the student perked up and “went to town” and excitedly explained their ideas.

Make it Practical

Instead of just verbally communicating our thoughts and ideas in our book discussion, we took time to practice what we were reading. For those who were “non-drawers”, we started with the Mike Rohde and Dan Roam approach of drawing and labeling a dot, circle, triangle, square, and line. Then we showed them Mike’s simple drawings of a fish, hamburger, dog, camera, and others, and allowed them to see how those simple shapes were building blocks to create drawings labeled with words (i.e. sketchnotes). Our faculty remarked how they were having fun drawing, even the one who initially said she couldn’t draw.

More Fun to Come

Our club will explore other “visual mind” books such as the SketchNote Workbook by Mike Rohde and Pencil Me In: The Business Drawing Book for People Who Can’t Draw, by Christina Wodtke. Dan Roam has written many books on the subject of drawing for visual thinking and communication. I was fortunate through my LinkedIn and real life connection with Mike Rohde (author of the Sketchnote Workbook) that I heard about his Back of the Napkin book. Grant Wright was the one who LinkedIn with me after I wrote a blog post about the Kindle Scribe vs. the Remarkable 2 and then later talked about Dan’s “Back of the Napkin” book. As in life, drawing helps us to create connections with people, ideas, and innovation.

Picture: Our KEEN Book Club in the School of Engineering. For the image observant, we ran out of hard copies of the book but have orders for more on the way.

About the Author: Andrew B. Williams is Dean of Engineering and Louis S. LeTellier Chair for The Citadel School of Engineering. He was recently named on of Business Insider’s Cloudverse 100 and humbly holds the designation of AWS Education Champion. He sits on the AWS Machine Learning Advisory Board and is a certified AWS Cloud Practitioner. He is proud to have recently received a Generative AI for Large Language Models certification from DeepLearning.AI and AWS.  Andrew has also held positions at Spelman College, University of Kansas, University of Iowa, Marquette University, Apple, GE, and Allied Signal Aerospace Company.  He is author of the book, Out of the Box: Building Robots, Transforming Lives.

Citadel Engineering: Focused on Students, Not Rankings

So proud of our The Citadel Engineering faculty and staff for the national accolades for their student-focused education efforts. We as a team are focused on delivering the best engineering education experience and value for our cadets and students. The rankings may follow but aren’t our priority or focus. 

🏆 Proud that US News has noted us as a top 25 undergraduate engineering program (non-doctoral) in the nation for the 13th straight year!

🏆 Proud that we are tied as the 4th highest ranked public non-doctoral undergraduate engineering program in the nation. (We are state-funded not federally-funded or private.) 

🏆 Proud to be the #1 engineering undergrad program (non-doctoral) out of the senior military colleges. 

We are humbled because all this is made possible only by the support we receive from our State of South Carolina, industry partners, and alum. Congrats again to our faculty, staff, and leadership team!

#GoDogs!

© 2023 Andrew B. Williams

About the Author: Andrew B. Williams is Dean of Engineering and Louis S. LeTellier Chair for The Citadel School of Engineering. He was recently named on of Business Insider’s Cloudverse 100 and humbly holds the designation of AWS Education Champion. He sits on the AWS Machine Learning Advisory Board and is a certified AWS Cloud Practitioner. He is proud to have recently received a Generative AI for Large Language Models certification from DeepLearning.AI and AWS.  Andrew has also held positions at Spelman College, University of Kansas, University of Iowa, Marquette University, Apple, GE, and Allied Signal Aerospace Company.  He is author of the book, Out of the Box: Building Robots, Transforming Lives.

Capturing Purpose and Passion in a Mission Statement

One of our faculty courageously stated in our meeting today something to the effect, “I hate to say it. But why do mission statements sound so generic and lack passion and love? As a parent, I’ve seen a lot of these college mission statements, and I’m not sure I’ve seen many that connect with my child or with me as a parent.” Today, we hit that head-on with the help of Dr. Sonia Alvarez-Robinson. We were honored to have such a seasoned strategy consultant work with our School of Engineering to begin our new strategic planning process. If we do nothing else but refine and capture what was shared today in our breakout session, we will have succeeded.

I’m not going to give a rundown of the steps we took today but talk more about why we took them and the energy that we felt. As people shared their personal “why’s” for why we teach to students, for example, someone literally talked about having love for our students and a love of the discipline they are teaching. We also heard comments that empathized with how our students engage with and experience their engineering curriculum at our institution. To that point, another faculty member added that we are starting a new class for first-year engineering students that combines all of our disciplines so that students can be exposed to each one before making a long-term commitment to a major.

We also shared how it is important to give them the fundamentals, but also show them how to work with others in other’s disciplines on big problems that must be solved on a bigger, and sometimes global scale. Some of our Executive Advisory Board members, who themselves are alumni and executives in large engineering firms, stated how important interdisciplinary collaboration in the real world is. Interdisciplinary collaboration is one of our four strategic priorities, along with innovation throughout the curriculum, infrastructure for growth, and inclusion and outreach.

At the end of the session, we gave everyone the chance to share one word about how they felt about our session developed by Dr. Alvarez-Robinson to co-create our vision and mission. Words such as encouraged, informative, insightful, tiring, helpful, collaborative, productive, interesting, contemplative, and inspired were spoken. My word? Energized.

Picture: Many of our School of Engineering Faculty and Staff with Dr. Sonia Alvarez-Robinson (in blue) at our Initial 5-Year Strategic Planning session. (Thank you Michael Kelsh for taking the picture for us.)

© 2023 Andrew B. Williams

About the Author: Andrew B. Williams is Dean of Engineering and Louis S. LeTellier Chair for The Citadel School of Engineering. He was recently named on of Business Insider’s Cloudverse 100 and humbly holds the designation of AWS Education Champion. He sits on the AWS Machine Learning Advisory Board and is a certified AWS Cloud Practitioner. He is proud to have recently received a Generative AI for Large Language Models certification from DeepLearning.AI and AWS.  Andrew has also held positions at Spelman College, University of Kansas, University of Iowa, Marquette University, Apple, GE, and Allied Signal Aerospace Company.  He is author of the book, Out of the Box: Building Robots, Transforming Lives.

V.E.R.B. Mentorship: Taking Action to Mentor Others in AI, Computing, and Engineering

If we are willing to admit it, we have all benefited from some form of mentoring, either informal or formal mentoring. I was reminded this summer of the joy I receive from mentoring at very little cost to myself. My story of mentoring is focused on Ronald Moore, a former summer undergraduate research student in my lab, who is now a current Ph.D. student at Emory in the Computer Science department working this summer as an Amazon Web Services (AWS) Applied Science Intern.

A Vision to Help Others Through Tech

I had met Ronald when he was probably in elementary school and reconnected with him during a summer while he was finishing his degree in Electrical Engineering at the University of Pennsylvania, where he had played at least one season on the football team. He didn’t have anything planned for the summer. I encouraged him to consider working in my research lab, the Humanoid Engineering and Intelligent Robotics (HEIR) Lab, at Marquette University in 2015. He hadn’t really had much programming experience, so I started him on a project to build small robot kits using Intel’s version of an Arduino, that could be used to teach middle school girls from underrepresented backgrounds how to build and program robots. It was a learning experience for Ronald. But he also learned the lesson that he could use technology to help others engage in and benefit from computing and engineering.

Expecting Success Even through Failure from Your Mentee

It’s important to raise the expectations of my mentees for what I expect from them. But more importantly, what they expect from themselves. My approach to mentorship is to be available for advice and guidance but to put the bulk of what needs to be discovered and done on the student I am mentoring. I find that my students can quickly come up to speed on subjects and often surpass what I know if they are given an engaging project and plenty of focused time to work. That summer seemed to spark Ronald’s interest even more in robotics. He had a few setbacks and sometimes progress was slow but he was encouraged to persist.

Resources and Relationships to Grow

Mentors realize that they don’t have all the knowledge and experience to effectively develop the mentee. I encouraged Ronald to go to graduate school. I think he took some time working with friends that had a startup but then decided to pursue a master’s in computer science, somewhat of a big change from pure electrical engineering. Ronald followed me to the University of Kansas and began his master’s research in human-robot interaction with me as his advisor. I taught him his first artificial intelligence class as well as an HRI class. It was exciting to see him progress. He also became involved in our IHAWKe (Indigenous, Hispanic, African-American, Women KU engineering) program, as a graduate student leader. He later applied to become a GEM Fellow (which I suggested to him), was selected, and eventually interned with IBM. I was a GEM Fellow myself, and so it was rewarding to see him apply and become a GEM Fellow as well.

A Belief Instilled and Pursued

As he discussed his future, I was able to share the pros and cons of pursuing a Ph.D. He applied and was selected into the Ph.D. program at Emory University in Computer Science with IBM as his sponsor. I could tell that, like myself, it was a challenge starting his program. What I really give him credit for was how he would contact me at least monthly to set up times that we could Zoom and ask any question he wanted. We often found some of that time either cheering or lamenting the KU Jayhawks or the KC Chiefs. Ron, to this day, continues to do his part as a mentee to initiate times when he wants to talk for advice or be a sounding board. I have benefited because he shares his research, but more importantly, I have the joy of seeing him grow as a young man and as an AI researcher.

A Goal: Going Beyond the Mentor

He saw my involvement with AWS through various educational projects and programs. This summer he decided to apply to become an intern at AWS. I’m proud to say that he was hired as an Applied Science Intern with AWS. He’a using his expertise but also expanding his research knowledge and space. Ron’s Ph.D. research at Emory is centered around developing methods that reduce bias in clinical risk prediction and treatment effect estimation algorithms. You can only imagine what he’s working on now. Let me just say, he’s going way beyond what I’ve done or know.

V.E.R.B. is an Action Word for Mentorship

So here’s how I help lead, inspire, and mentor others: V.E.R.B., an acronym that I developed and have used over the years.

VISION – help them see the possible and dream of the unseen in their own lives and the lives of others.

EXPECTATION – give them reasonably high expectations for them and positive expectations of success, even if there are slight setbacks along the way.

RESOURCES/RELATIONSHIPS – provide them with the resources they need to succeed and connect them with others who will help build up their experiences and expertise.

BELIEF/BELONGING -believe in them before they even believe in themselves, know that they belong in their chosen field, and continue to cultivate their own belief in their capabilities, potential, and possibilities.

To all my past and current mentors, I continue to dedicate myself to mentoring others. And those who want to be mentored by me only need to contact me and show the type of commitment to learning and growth that Ronald continues to show. Ronald is using his research abilities to help others avoid problems with machine learning bias and to benefit from how ML can be used to help clinicians and nurses heal others more effectively. And that’s a mentoring V.E.R.B. worth acting on.

Picture: Ronald Moore in front of his research poster at the 2019 ACM/IEEE International Conference on Human-Robot Interaction in Daegu, South Korea, as a student of mine in the Humanoid Engineering and Intelligent Robotics (HEIR) Lab at the University of Kansas.

© 2023 Andrew B. Williams

About the Author: Andrew B. Williams is Dean of Engineering and Louis S. LeTellier Chair for The Citadel School of Engineering. He was recently named on of Business Insider’s Cloudverse 100 and humbly holds the designation of AWS Education Champion. He sits on the AWS Machine Learning Advisory Board and is a certified AWS Cloud Practitioner. He is proud to have recently received a Generative AI for Large Language Models certification from DeepLearning.AI and AWS.  Andrew has also held positions at Spelman College, University of Kansas, University of Iowa, Marquette University, Apple, GE, and Allied Signal Aerospace Company.  He is author of the book, Out of the Box: Building Robots, Transforming Lives.

Safely Exploring Generative AI for Faculty and Student Learning

How is generative AI going to impact your career? How is it going to impact engineering educators and students’ learning experience? We are planning a faculty design thinking session to explore Generative AI (GenAI) for how it can be used to help students learn. Why? Everyone is curious about it, from students to CEOs, and we are all trying to figure out how it connects to what and how we teach, and how we can create value for our students by using GenAI. We are trying to identify the opportunity it presents for engineering educators and how we can scale it best for impact. Sound familiar?

What do we mean by “safely?” We recognize that most faculty may not have a background in AI and rely on what they hear from others. Many teachers are worrying about how to keep students from using it to cheat. There are many other fears that faculty and students have about AI. There is a feeling and fear of being left behind the technology curve and losing relevance in their future or current careers. Many students that are near graduation are worried they are not prepared for an AI-enhanced workforce. Faculty that have not been in the engineering industry for a while or possibly ever, may be unaware how GenAI is impacting the workforce or the military. Also, by “safely” we want to make sure that as educators, we make sure we limit the exposure of toxic GenAI output, respect intellectual property, and discern accurate and honest content. Faculty and students must learn how to use GenAI responsibly.

We are going to get all of these issues out on the table in a comfortable and open intellectual space. We are going to use design thinking to empathize with faculty and students. We are going to clearly define the needs, pains, and potential gains that faculty and students have related to AI in general and specifically to GenAI. We’ll take time to brainstorm potential solutions or “products.” We will be able to build some teaching prototypes and feedback on our ideas. Trust me, it will be a “safe” space to explore the technology’s impacts and learn how we can tackle the challenges together.

We are delighted to have Christina Hnova, from the University of Maryland Academy for Innovation and Entrepreneurship, facilitate our session. I met Christina through my past instructor at the Stanford d.school Teaching and Learning Studio, Dr. Leticia Brito Cavagnaro. Through Amazon Web Services (AWS) Machine Learning University and AI Educator Enablement Program, we have been able to begin preparing many of our faculty in the School of Engineering to teach and integrate AI. But we are also aiming to help faculty in other schools, including the Humanities, Business, Education, and Science, explore GenAI with curiosity, connections, and value creations for an interdisciplinary AI student learning experience. Come join us!

Picture: A curious learner with Kathleen, one of my Humanoid Engineering and Intelligent Robotics (HEIR) Lab undergraduate research students, during an AI-enabled humanoid robotics outreach event when I was at Marquette University.

Acknowledgments: Thanks to KEEN and the Kern Family Foundation for their support!

© 2023 Andrew B. Williams

About the Author: Andrew B. Williams is Dean of Engineering and Louis S. LeTellier Chair for The Citadel School of Engineering. He was recently named on of Business Insider’s Cloudverse 100 and humbly holds the designation of AWS Education Champion. He sits on the AWS Machine Learning Advisory Board and is a certified AWS Cloud Practitioner. He is proud to have recently received a Generative AI for Large Language Models certification from DeepLearning.AI and AWS.  Andrew has also held positions at Spelman College, University of Kansas, University of Iowa, Marquette University, Apple, GE, and Allied Signal Aerospace Company.  He is author of the book, Out of the Box: Building Robots, Transforming Lives.

Using Entrepreneurial Mindset and Making to Spark More Accessible AI

What do you think this is a picture of? How would you imagine it connects with a student learning artificial intelligence? A little more on that later but let me share a little on the process of why and how I arrived at this little contraption to teach some AI and machine learning concepts.

KEEN MakerSpark: A Framework for Developing Entrepreneurial Mindset Activities

This week I participated in the KEEN MakerSpark workshop. We looked at how to use “making” and the three C’s of an entrepreneurial mindset (curiosity, connections, and creating value) to improve our engineering curriculum. Since I teach AI and machine learning, I was curious how I could use “making” to visually and tactile”ly” demonstrate how machine learning works to a college student or even a child. In this context, “making” refers to physically making something with your hands. In the context of the 3 C’s, the making is driven by a student’s curiosity, their need to make connections from disparate information, and prototyping a concept or an idea to create value.

Deconstruct/Reconstruct Troublesome Knowledge

In teaching, we often want students to learn a new concept. But there is more to teaching a concept then giving a student a definition, equation, or example. We need to deconstruct all that we know that the student knows and how they arrive at that concept. Troublesome knowledge consists of those engineering or computing concepts that our students seem to struggle with the most. Working backwards, starting at this troublesome knowledge, we then design a learning activity using objectives with observable outcomes and ways to measure their learning.

I identified what makes some introductory AI knowledge “troublesome.” Students may not know that machines can “learn”. Students may not understand the different ways machines learn. Yes, at this point I could put up some complex math equations that explain machine learning, but what does this mean to a middle school student trying to learn the basics in a visual and tactile manner?

Defining Success and Struggling in Learning

Working backwards, we can define what concept we want to and things we can observe that shows that they have mastered the concept or not. These learning objectives should state clearly what we want the student to learn, by when (e.g. end of class), and what’s the observable way of telling they learned it. A concept in AI that I want students to learn is what is unsupervised machine learning classification versus supervised machine learning classification. They are struggling if they can’t identify what it is visually.

Modeling the Knowledge Using Analogies, Sketches, Data Physicalization, or Stories

To ask myself how I could model this knowledge, I thought of analogies to unsupervised/supervised machine learning classification. I thought of analogies, metaphors, similies, and stories and drew sketches. I won’t list them here, but it involved me drawing sketches with stick figures and drawing what I know about this topic. I then brainstormed ideas about how to physically show the data as it flows through a machine learning classifier or neural network, or some other teaching tool or experimental model. I picked one of the example ideas and decided I would make a simple “maker” exercise for students to try. Hence, the “contraption” I made in the picture with a tube, holes, and small BB and marble-sized balls of different colors. The fun part of this process is that the instructor gets to “make” a low-fidelity prototype proof of concept that will guide what the instructor will then instruct the students to “make,” but not necessarily the same prototype. In other cases, the instructor’s prototype will be the basis of the learning activity the students use. For example, one of the faculty, Mark Ryan, created a prototype game to teach “for” and “if” loops for non-computer scientists.

Prompting the Student to Make Prototypes and Use them to Assess their Learning

After explaining the concept of unsupervised/supervised machine learning classification, I would prompt the student to make something that demonstrates the concept. I wouldn’t want to give them the answer but be there to give them hints and clues and positive encouragement to think of analogies and metaphors themselves. I would instruct and encourage them to use the low-fidelity prototype materials (a.k.a. craft supplies) to build their prototypes and test them on other students. If I’m being kind of vague, it’s because I want to try this out on some of our students this fall to see what I learn first.

Innovating throughout our Engineering Curriculum

I am grateful for the many teaching innovations that I have been able to experience and learn through workshops like Stanford’s d.School’s Teaching and Learning Studio and the KEEN Network’s MakerSpark I just went through in Boston, which I learned these concepts through that I’m able to share. As an engineering leader, I’m grateful that the Kern Family Foundation provides these opportunities for all of our faculty to learn to innovate in their classrooms from other faculty in the KEEN Network. The opportunity is there, and it’s up to us to seize them and make them a reality in our students’ learning experiences.

Picture: A low-fidelity, hands-on teaching model for students to use data physicalization and making to learn the concept unsupervised and supervised machine learning classification.

© 2023 Andrew B. Williams

About the Author: Andrew B. Williams is Dean of Engineering and Louis S. LeTellier Chair for The Citadel School of Engineering. He was recently named on of Business Insider’s Cloudverse 100 and humbly holds the designation of AWS Education Champion. He sits on the AWS Machine Learning Advisory Board and is a certified AWS Cloud Practitioner.  Andrew has also held positions at Spelman College, University of Kansas, University of Iowa, Marquette University, Apple, GE, and Allied Signal Aerospace Company.  He is author of the book, Out of the Box: Building Robots, Transforming Lives.

Affirm Action to Empower Our Children’s Engineering and Computing Education

Who empowered or encouraged you growing up to pursue your education? I can name many, from my elementary school teachers, Sunday School teachers, parents, and older siblings. My Mom only had the equivalent of a third-grade education in Korea and learned to read English at an elementary school level. But when I would come home from school, she would say to me, “I believe Andrew makes all A’s.” She continued saying that up until college. She instilled academic confidence in me at a very early age. My Dad had a high school education growing up in Connecticut. He continued to learn mechanics in the Army by daily reading newspapers and magazines like Popular Mechanics and Popular Science. He could only afford old cars but would rebuild the engines all by himself in the backyard so he could transport all six of us kids.

My Sunday school teacher, Sharon Scoggin, was one of the few people I knew outside of school that went to college. I have known her since I was three years old. She and others would have us read Bible stories from the King James Version, so little did I realize I was reading at around the twelfth-grade level by the time I was in second grade. My oldest brother, Robert, led us down the path of college possibilities by enlisting in the Air Force and later being sent back to study electrical engineering at Kansas State, near our hometown. I remember the first time I saw his little LED circuit he created with Boolean logic, and I was fascinated. I decided I wanted to become an electrical engineer like him.

By the time I reached high school and took the PSAT test, I did really well. I was getting recruitment letters from Harvard, Stanford, MIT, Brown, and other places. I started to apply to Harvard and even went through the alum interview process. But I never completed the application. My Dad suggested I go to KU just down I-70, and then maybe go to an Ivy League school later. I guess he was scared we couldn’t afford it on his $100 a week paycheck and his $300 a month Army retirement check. He didn’t know much about college loans or scholarships. He pointed out that my other brother had gone to KU to study aerospace engineering, worked as an engineer for a couple of years, and then went to MIT to get two master’s degrees.

I sometimes wonder what would have happened if I had completed my application. Would I have been accepted to Harvard? Who knows. I do know that I’ve lived a blessed and prosperous life going to public schools all through high school and a public university. I have benefited from policies and benefactors that encouraged companies and institutions to recruit, hire, and retain individuals from various racial and ethnic backgrounds. Hey, I even had Steve Jobs, co-founder of Apple, see the benefit of hiring black engineers to work there, so much so that he hired me to help Apple do that. That’s a lot from one of the most impactful innovators we have seen in our modern day.

I grow concerned not so much about how policies are changing but about the message it gives to our young people. Our message to our young people should be that they are welcome and belong at our most elite institutions as well as all the other institutions that will provide a world-class education, starting with elementary school to community college to universities. The latest policy changes worry me that they will impact not only our educational thoughts and policies about race but also those related to gender. I want my daughters to always know that they belong in the engineering and computing field. But I also want other’s children to have the same types of opportunities that my children have because of the privileges I’ve been able to earn with God’s help. I had to sign a waiver to have my son be able to take Calculus in high school in Atlanta because as a black boy they didn’t think he could succeed in it (which, of course he did and went on to get a computer science degree). That’s why I am passionate about helping other parents and children get excited about learning engineering and computing, and I hope you will consider doing the same.

Remember, the institution one studies at does not necessarily equate to happiness, success, or a good life. I and others like me are a testament to that. From someone who as a child grew up in a low-income first-generation home, I know that as a fact. My Mom didn’t have a college education or even a high school diploma let alone a degree from an Ivy League school. But she had something more in the spiritual realm. As my Sunday school teacher had me read as a child, “Blessed are you who are poor, for yours is the kingdom of God.”

Picture: William Farr and me learning on an Apple II computer at Junction City High School back in the ’80s.

© 2023 Andrew B. Williams

About the Author: Andrew B. Williams is Dean of Engineering and Louis S. LeTellier Chair for The Citadel School of Engineering. He was recently named on of Business Insider’s Cloudverse 100 and humbly holds the designation of AWS Education Champion. He sits on the AWS Machine Learning Advisory Board and is a certified AWS Cloud Practitioner.  Andrew has also held positions at Spelman College, University of Kansas, University of Iowa, Marquette University, Apple, GE, and Allied Signal Aerospace Company.  He is author of the book, Out of the Box: Building Robots, Transforming Lives.

Real Intelligence: Remembering the Value and Superiority of Humans over Machines in the Age of AI

“The only way AI will cause humanity’s existence to cease is if humanity only primarily invests in AI but fails to value and invest in humanity itself.” – Andrew B. Williams

The narrative for AI, particularly generative AI, is being set in the media and national stage. Some say it will eventually cause our civilization to end. It will cause white-collar and knowledge-worker jobs to slowly disappear. No one is safe. So we say. Also, the narrative says there is an AI arms race, and we must invest as much capital as possible into this new technology.

One thing saddens me about this narrative. There are so many more “things” that are so much more capable and amazing than generative AI. So many more things worthy of our investment of time and money. They are not actually things. They are individual humans themselves.

I appreciated the value and superiority of humans afresh listening to Dr. Bobby Kasthuri, neuroscientist at Argonne National Labs, speak at the KEEN National Conference in January 2023. Although computer scientists have created artificial neural networks very roughly modeled after how an aspect of the brain works, no one has actually mapped the connections in the human brain. One individual human’s brain has about 100 billion neurons that, each have 1 to 10,000 connections to other neurons, creating a quadrillion connections in a single human brain. That’s 100 to 1,000 times more stars in the galaxy!

Dr. Kasthuri is seeking to build a supercomputer system that’s large enough and powerful enough to map all of the connections in the human brain. He believes this map of our connectome will lead to an understanding of the physical basis for all of our memory, skills, hopes, thoughts, and dreams, much like the mapping of the human genome has done for understanding the genetic basis of life. And also, we may be able to determine how we experience the misfiring of the brain that produces pathological effects, such as autism and schizophrenia. He worked on mapping the connectome of a mouse. Mapping the human genome resulted in about 200 GB of data. Mapping the mouse connectome is about 2000000000 GB of data. Imagine how much data mapping the human connectome will produce.

Recently I watched a 60 Minutes story on AI. The reporter seemed so amazed at what the generative AI (genAI) model produced. They later checked the books that the genAI model had recommended and found that they were made up and not real. Also, recently, I read that a comedian is suing a company for its genAI model because it summarized her book without ever purchasing it. Could it be that the, should I say, “scam” of some genAI is that it’s “stealing” the data produced using existing human creative works of art, literature, audio, video, etc., to recreate “original,” AI-generated pieces? Is that “amazing,” or is it unethical?

I could end there, but I wanted to say that we need to be re-amazed by how amazing real humans are. As Dr. Kasthuri said, yes, an AI program can beat a human at chess, but an AI-enabled robot can not walk up to the table, sit down, move pieces, and think the way a real human can. In a future blog post, I plan to write about the environmental impact involved in training these genAI models, an issue that was brought to light by Dr. Timnit Gebru, formerly of Google, and others. But with all the power, energy, and natural resources required to train one of these large GenAI, or Foundation model, needs, the human brain only operates on about 20 Watts of power. Less power than most light bulbs. In contrast, the supercomputer Dr. Kasthuri plans to build will require the power from an entire power plant.

So let’s just not only tout the benefits and possibilities of generative AI and say we must invest billions of dollars to develop and sustain it. Let’s not forget about the human child down the street, one that has incredible brain capabilities but living in poverty, or even in another country that is much more amazing, intelligent, and worthy of our investment into their education, well-being, and future than a machine that copies our original work so others can tout it as their own. Let’s invest billions in our own human children. One of those children may grow up with a big dream to map the connectomes of the human brain to help others learn and treat brain disease. One of those might grow up and become a Dean to lead others to become engineers and a leaders that build a better world.

“It’s more important to invest in, encourage, educate, and empower a human child than it is to invest in a machine, computer, or algorithm.” — Andrew B. Williams

Picture: Dr. Narayanan “Bobby” Kasthuri and me at the 2023 KEEN National Conference in Atlanta, where he spoke on mapping and understanding the brain so that we can learn, teach, and cure diseases of the brain. His fascinating talk can be found here.

© 2023 Andrew B. Williams

About the Author: Andrew B. Williams is Dean of Engineering and Louis S. LeTellier Chair for The Citadel School of Engineering. He was recently named on of Business Insider’s Cloudverse 100 and humbly holds the designation of AWS Education Champion. He sits on the AWS Machine Learning Advisory Board and is a certified AWS Cloud Practitioner.  Andrew has also held positions at Spelman College, University of Kansas, University of Iowa, Marquette University, Apple, GE, and Allied Signal Aerospace Company.  He is author of the book, Out of the Box: Building Robots, Transforming Lives.