Many students look at drones as cool toys to play with, not an emerging technology with several career possibilities. Drones are being utilized in several industries and are making huge impacts on society. Below are a few examples:
Zipline (https://flyzipline.com), a medical product delivery company, is revolutionizing the way medical supplies are transported to medical clinics in Africa.
AgEagle Aerial Systems (https://www.ageagle.com/drones), manufactures high performance drones capable of capturing ultra-high resolution images and producing actionable data analytics for farmers.
From an educational perspective, exposing students to drone technology in the classroom provides an innovative learning experience. In addition to having students explore the many career possibilities in this fast-growing, multibillion-dollar industry, drones can also serve as an educational tool to teach computer programming. Drones also present many opportunities for students to practice 21st Century Skills, such as communication, collaboration, critical thinking and problem-solving. Last year I implemented Apple Swift Playgrounds and the Parrot Education Subscription to teach my students how to program and pilot a Parrot Mambo drone. Students learned how to program a drone to takeoff, land, move in all directions, make aerobatic figures, and even control accessories. It was a successful hands-on learning experience for my students and they had the opportunity to see first-hand the cause and effect of their programming. Although there were many successes, there were also failures, providing authentic opportunities for learning. For example, one of the challenges I gave my students was to program the drone to fly through an obstacle course. This challenge posed a lot of struggles for my students; but every time they failed, they worked to troubleshoot their programs and figure out why the drone was not doing what they wanted it to do. They then fixed their code and tested it again. The perseverance that I witnessed by my students during this experience was truly amazing.
Drone resources that I use in my classroom can be found at https://bit.ly/2XlLkBI. I encourage you to consider incorporating drones into your classes. They are engaging and a great opportunity for learning computer science.
I have been thinking about the phrase “it’s easy,” and how hurtful that phrase can be. Just because something is easy for one person doesn’t mean it is easy for everyone. And conversely, just because something seems like it will be hard doesn’t mean it will be hard.
Maybe you think someone doesn’t have a lot on their plate compared to you. But maybe their plate is smaller than yours and doesn’t have a lot of room to begin with. Or maybe their plate is paper, and their flimsy paper plate can’t hold as much as your sturdy ceramic plate can.
Sometimes “it’s easy” is deployed in a very personal way – something I think is easy but someone else might not find easy. For example, I think functions are fairly straightforward – easy, even – but for many students they are one of the most challenging parts of programming. Even when I am frustrated as a teacher, telling my students that it is easy doesn’t help them understand, it only makes them feel worse about how challenging they find it.
When I taught middle school, a teacher down the hall had a big sign in her class that said, “YET.” Her philosophy was that when students did not succeed, it was because they had not yet mastered the material. What a forgiving and empowering view of learning: it isn’t that students are deficient, it’s that they aren’t strong yet. Yet is a very growth mindset point of view.
On the flip side, “it’s difficult” can be just as arbitrary. One teacher I know believes that nothing is truly difficult (even functions!), that if students are struggling, it means we aren’t teaching it very well.
One example of something that seems hard is recursion. We have a shared belief that recursion is hard. It means that students come to believe that recursion is hard. Yet at its most basic, the idea that a function can call itself isn’t that hard. And especially for problems that are recursive in nature – the Fibonacci sequence for example – the recursive solution is obvious, and is what students will natively come up with if asked to figure it out.
Thinking things are hard or easy can be a barrier for students – scaring them or preventing them from accessing things we perceive to be too hard, or making them feel bad for not grasping things that are “easy.” Hopefully we can all achieve the goal of making learning accessible – not too hard and not too easy.
I’ve been fortunate enough to have some great conversations about what CS teachers need to know over the last year. Stakeholder groups, including teacher education programs, state department of education specialists, CS and education faculty at higher education programs, are all working to figure out how to develop sustainable models of preparing computer science teachers to meet the growing demand for CS teachers.
Some of the conversations are driven by and informed by the current process to refresh the CSTA and ISTE Standards for CS Educators. In January 2019, CSTA and ISTE began work on these standards, which seek to set clear goals for CS teachers know and be able to do in the classroom, serve as aspirational goals for CS teachers, and establish benchmarks for those providing learning opportunities for CS teachers. The second draft has now been released and is available at csteachers.org/page/standards-for-cs-educators for comment until October 11th. The final version is expected to be available by the end of 2019.
Other conversations have been very focused on practical matters, including what should be included in a computer science methods course. Here is a list of items that education and computer science faculty brainstormed during a workshop sponsored by the Maryland Center for Computing Education this summer. Workshop participants drew on their experiences teaching methods courses for generalist educators (often at the elementary and middle school level) and for secondary educators seeking licensure in a specific topic.
CS Subject Matter Knowledge (SMK), in particular for generalists as they may not have had a standalone course in computer science
CS Pedagogical Content Knowledge (PCK) – how to teach computer science
Evaluating curriculum – how to choose a curriculum that aligns with relevant standards, is relevant to students, engages students, etc.
Unit Planning – how to create a set of lessons that build on each other to achieve learning objectives
Understanding and aligning with student standards (e.g. CSTA K12 Standards)
Common misconceptions in learning computer science, including how students construct models of how a computer works
Classroom management, especially managing instructional technology and devices
Formative and summative assessments of computer science learning
Designing instruction for all students, including those with learning or physical disabilities and those typically underrepresented in computing
Understanding professional codes of ethics for computer scientists and the impacts of computing
Supporting students in learning academic vocabulary as well as reading in the content area
Teaching methods for computer science, including strategies such as peer instruction, POGIL, pair programming, worked examples with subgoals, Parson’s problems, and many more
Integrating computer science in other content areas, in particular for generalists
Field experiences – a teaching placement in a school that includes computer science
Of course, this is not an exhaustive list of what might be included in a CS methods course, nor would all of these topics necessarily be included in a single methods course. Teacher educators may need to consider their local context, including where there is overlap with other areas of their education program and the state licensure requirements. But, it is a start and I’m looking forward to having more conversations in the future with stakeholders working on developing sustainable programs for computer science teachers.
At Google, I lead the Outreach team for Computer Science and Digital Skills Education, which means I get to support CSTA and other great organizations working to broaden access to CS education. In this role, I often find that educators are especially interested in learning more about Google employees (we call them Googlers) who use computer science, so that they can better prepare their own students for the workplace.
I recently undertook a non-scientific study and polled a small sample of 15 Googlers* in technical roles (nearly all engineers) about their K-12 CS education experiences, in hopes that they’d provide some advice I can pass onto CSTA members. Here are seven themes that emerged:
1. Encouragement is really important and comes in many forms.
Given the body of research demonstrating the importance of encouragement in helping students persist in CS education (e.g., this white paper), it’s not surprising that Googlers talked a lot about receiving encouragement. This came mostly from teachers and parents. Interestingly, friends/peers were a pretty distant third place. Googlers gave lots of examples of how educators provided them with valuable encouragement, including:
My AP CS teacher encouraged me to apply for an NCWIT award, which I won. I joined the Facebook group and immediately felt more included in the national CS and specifically women’s CS community.
My high school math teacher was my biggest cheerleader when it came to CS. He had a pretty limited coding background himself, but had the foresight to recognize that CS was the next big thing and that I was good at problem solving and puzzles.
2. Share opportunities and challenge your students to stretch themselves.
While some Googlers didn’t know about CS opportunities or didn’t have people in their lives with access to that information, several mentioned that teachers often passed on valuable information about internships and scholarships. Some said that their teachers challenged them to stretch themselves in ways that they might not have otherwise considered.
My teacher pushed me to try the next thing and keep investing in my CS education.
My teachers shared available IT-related internship opportunities in the area.
Even if they don’t feel qualified, get your students to apply for scholarships, summer camps, and other opportunities. Most will feel hesitant even if they are qualified! Consider offering extra credit for stretching themselves.
3. Make computer science relevant. Personalize the education.
Googlers shared that effective teachers used a wide range of examples and projects, tying content to students’ interests, to make CS feel relevant. Practical applications were especially inspiring, as were real life demonstrations of programs to show CS in action. Some Googlers called out the importance of rigorous CS content or having flexibility for advanced students to explore and learn further on their own.
The teacher built a class management system that would randomly pick students to answer questions, and would automatically grade them at the end of the term based on their answers.
Leveraging CS to run low-cost experiments can show its relevance.
Find and share exciting examples through YouTube videos related to topics of interest.
Don’t be afraid to let the students have freedom to do things their way — it’s messier, but empowers creativity.
4. Connect lesson plans to WHY students should learn CS.
Related to the above theme, Googlers gave examples of how successful teachers not only taught them how to do things, but also helped them understand why they were learning those CS concepts.
My best CS teacher made the lessons relevant. He always highlighted why we were learning specific concepts.
Begin by posing problems first, then introduce the tools to solve them. This encourages creativity and divergent thinking, making it easier for students to remember the applicability of the tools.
Connecting theory with their practical industry experience made it much more tangible why we were learning CS.
5. Foster collaboration, sharing, and connections.
The importance of teamwork, community, and sharing work samples were mentioned by several Googlers. By inviting students to share their work, teachers not only encouraged peer-to-peer teaching and learning, but also provided validation and recognition. Similarly, building communities fostered friendships among peers with similar interests.
Seeing advanced work done by peers encouraged me to learn more.
[My teacher encouraged me by] letting me show my finished programs.
Peers played an enormous role, as we were programming together to solve Project Euler problems.
My teacher sponsored a computer club, which introduced me to other students with similar interests.
One friend took the intro course [with me], and her friendship was key to me staying in CS.
6. Teacher support helped students overcome various challenges.
Googlers shared a host of challenges they faced, and in some cases, how teachers helped them overcome these barriers. The most common themes were: lack of CS as a core subject or unavailability of courses; insufficient computer or internet access, especially in rural areas; lack of exposure to CS and mentors; facing gender stereotypes and being made to feel out of place as a girl; and general low self-confidence or impostor syndrome.
Resources were limited, but my teacher pointed me towards opportunities that were available (university classes, online forums and Q&As, etc.).
I had a couple of big missed areas due to being self-taught.
My biggest challenge was lack of structured content beyond intro level.
The first time learning something it can seem impossible, but revisiting makes it clearer. Keep reteaching tough concepts to struggling students — it might eventually click.
7. Keep up the great work!
Finally, Googler advice for CS teachers included some gems that didn’t quite fit the themes above, but that I felt compelled to share as they aligned nicely with CSTA’s work of supporting CS teachers through professional development, community, and inspiration:
Keep growing as computer scientist yourself!
Have a growth-mindset approach to teaching (and learning).
CS classes changed my life. Your classes will most likely change someone else’s.
* Here’s more information about the 16 Googlers who completed my survey: 80% are engineers with varying years of experience. There was a diverse representation across age ranges and also race/ethnicity, and 60% were female. On average, the Googlers were first exposed to CS at age 14 (responses ranged from 7 to 18), though they reported really enjoying CS at age 17. Not surprisingly, nearly everyone described multiple points of exposure, with in-class learning and self-learning by far the most commonly cited. Learning from family/friends, after-school programs, informal programs (libraries and youth-serving organizations), bootcamps, and internships were also mentioned. Over two-thirds of Googlers identified a teacher who played a critical role in their learning: most mentioned a CS/programming teacher, but mentors also included computer lab staff and a librarian.
Two pieces of important and good news have come out recently about the state of, and opportunities for, the participation of young women in computer science. The first is the participation of women in the 2019 computer science advance placement exams; the second is the announcement of this year’s Aspirations in Computing awards program organized by the National Center for Women & Information Technology. Together, they are an indication of how far we’ve come as a community in recent years in embracing the opportunities for young women to study computer science in high school, and in providing encouragement and support to continue these studies in college.
The participation in the computer science AP exams, like most everything else associated with computing, has exploded in recent years, and the participation of young women has outpaced the overall growth. As is summarized in this article, the total number of women taking CS AP exams in 2019 grew 32% since last year, to over 48,000, and the percentage of women among all test-takers increased to over 29%. The growth in the number of women taking AP CS is nearly five-fold in just four years, and the percentage of women which had hovered in the high teens for years has grown dramatically.
Much of the growth of enrollment in high school computer science, and in CS AP exams, is due to the CS Principles course. As is described here, in just three years since this course and exam were introduced, the number of students taking CS Principles AP has skyrocketed to over 96,000, which now is nearly 60% of the total CS AP test takers. And the participation of women students in the CS Principles AP exam outpaces the overall CS AP participation by women, at 33%. This still is far from half but is approaching a tipping point!
A great accompaniment to the quickly growing participation of young women in high school computer science courses is the NCWIT Aspirations in Computing Program. The Aspirations program has grown over recent years to include not only awards that have become well known, but also community elements that stretch down to lower grades and up to the university level. Here I’ll just focus on the upcoming awards program. The Aspirations awards are a great opportunity to recognize and encourage young women who are actively engaged in computing at the high school level. By a system of competitions and awards that now is conducted in 79 separate regions across the US, this program provides opportunities to recognize many young women annually (nearly 14,000 since 2007!), as well as their teachers. Having been to several regional Aspirations awards ceremonies, it is inspirational to see the impact of this program on the young women and on their families. Please encourage your students to apply to Aspirations, and support them in taking courses that lead to the CS AP exams!
Don’t get me wrong, being retired is the best job ever (with teaching a close second!) but I must say I feel very lucky to be able to stay active in the computing education community. Particularly, being the co-chair of the ACM Education Board and participating as a CSTA Board member has given me opportunities to keep learning and participating with people around the world.
I was invited to attend the ACM SIGCSE China conference in May, 2019 in Chengdu China https://www.acmturc.com/2019/en/SIGCSE.html(and yes, the panda bears were very cute). I was part of a panel which was titled Computer Education Research. Panelists included Junlin Lu (China), Juan Chen (China), Jane Prey (USA), Steve Cooper (USA), Andrew Luxton-Reilly (New Zealand), Brett Becker (Ireland), Bo Yang (China). While this may sound like a research discussion, we ended up talking about various scenarios for teaching computing in primary grades (aka K-12.) There were many opinions and ideas around the availability of resources, diversity and engagement. We discussed the different languages used, the various approaches, etc – takeaway #1: People from around the world ask the same kinds of questions we do on how to best teach their students.
What I enjoyed most were our conversations on how “easy” vs “challenging” the content should be and if programming/coding should be the principle deliverable from the class. Particularly interesting comments included: if it’s too easy, what are they learning?, how to keep students interested in doing something challenging?, how to challenge students and have them feel successful and rewarded for doing the hard work?, how to recognize when to push and when to hold back, how to have students add to their ability to solve problems? My takeway #2 is that our group (panelists and attendees) believe that computing in school should be fun, that fun does not mean easy, that fun should include moments of reflection and work, that work should be fun.
Takeaway #3: there are many smart and passionate people around the world working to answer these questions. I am very lucky my grandchildren will be taught by such people.
I’ve no doubt that good CS education involves finding some motivating contexts for getting the ideas across, and for pupils to get to grips with programming. Lots of teachers have found their pupils highly engaged through creating games and animations, or through interacting with the real world through physical computing and robotics, or, perhaps more unusually, through algorithmic art or composing music. I think we could make a good case for adding some data science into this mix, getting pupils to do a little visualisation and exploratory data analysis, and through this starting to answer some genuinely interesting questions.
When we wrote the English computing curriculum, we included some explicit references to working with data: 7-11 year olds are taught “collecting, analysing, evaluating and presenting data”, and 11-14 year olds “undertake creative projects that involve selecting, using, and combining multiple applications, preferably across a range of devices, to achieve challenging goals, including collecting and analysing data.” Or at least they’re supposed to. CSTA’s standards go quite a bit further, with a whole strand given over to data and analysis, with a clear sense of progression and ambitious targets for high schoolers like “Create interactive data visualizations” and “use data analysis tools and techniques to identify patterns in data representing complex systems”. I worry that we’ve put so much emphasis on coding that these crucial skills, and the consequent understanding gets overlooked in too many schools. It needn’t be this way. Indeed there’s plenty of scope for doing this data visualisation and analysis with code.
I’ve been thinking recently about how we can take the foundations / application / implications (that’s roughly computer science, IT and critical digital literacy) model that underpins the English computing curriculum and apply it to related (and some unrelated) subjects, to help promote a broader and more balanced approach to curriculum design. We can use this model for thinking about data science in schools.
If we’re serious about pupils’ learning data science, then I think we need to lay the foundations with some old school probability and statistics: typically these are already part of the math curriculum, but there’s so much more we can do here when we let our pupils use computers for this, from simulating dice rolls, through plotting graphs to calculating summary statistics for some big datasets. All these things can be done by hand (‘unplugged’?), but once pupils have an idea of the techniques, they can concentrate on selecting and using the right tools, and making sense of the results if they use technology to automate the automatable parts of the process – it’s far more interesting and useful to be able to make sense of a scatterplot (for example) than to be able to draw one by hand.
I’d also want pupils to apply this knowledge to some interesting problems. In elementary school, I’d look at opinion polls or other surveys as a way in to this, perhaps getting pupils to work collaboratively at coming up with good questions – agree / disagree Likert scales are a good starting point, and then exploring what they can learn by slicing the data they collect: is there any difference between boys’ and girls’ enjoyment of school subjects in elementary school (and is there any difference in high school…)? Later on, I’d start looking at time series: weather data is great for this. In the UK we’ve open access month on month meteorological data going back over 100 years, and a comparison of temperatures for the last 30 with the previous 70+ makes a persuasive case. Later still, I’d get pupils looking for patterns and relationships in big (or biggish) datasets: sports fans might like to play with accelerometer or GPS data from micro:bits, wearables or phones: can they work out what sport someone was playing from the datafiles (or a visualisation of them)? Could a machine do this? Big, public, anonymised datasets could be linked very powerfully to some social studies topics: what are the links between gender, ethnicity, education and income? Or pupils could learn about text mining techniques and apply these to their study of English: are there quantifiable differences between the vocabulary and grammar of Hemingway and Morrison? Or between Obama and Trump?
Even more importantly, I’d like pupils to think through some of the implications of collecting and using data as freely as we do. Coming back to my elementary school survey idea: what questions shouldn’t we ask one another? What questions shouldn’t we answer? Does it matter if your name is attached to the answers? In one day at school, how much data does a pupil generate (attendance, grades, cafeteria, accessing the internet, CCTV, online learning, behaviour management, etc…)? What happens to all this data? What could you discover about a pupil if this was all linked together? Does anyone mind? How much do internet service providers, search engines and email services know about a user? What do they use this for? Again, does anyone mind? If big tech firms provide the wonderful services they do for free, how have they got to be some of the most valuable companies in the world? The English computing curriculum includes teaching pupils ‘new ways to protect their online identity and privacy’ – what should we include here?
Some of this certainly should be part of what our pupils learn in their school computing lessons, but lots of it provides ample opportunity for cross curricular links, with math, social studies, civics and even sports! I think we as CS teachers gain so much through showing how relevant coding can be to the other things our pupils study.
By Dan Blier, CSTA Board of Directors (District
It is that time of the year when we re-open our doors to our
students for another school year. With
that in mind, this is a great time of the year to start thinking about what new
computer science resources students will be introduced to this year. As a district computer science curriculum
specialist for Plano Independent School District in Plano, Texas, it is my role
to work with teachers from Prekindergarten (Pre-K) through 12 grade to build a
vertical computer science program.
Building an equitable computer science program takes a great deal of planning and collaboration with others. Input from teachers, campus and district administrators, parents, the District Board of Trustees, and community partners is an important part of this process. The process requires taking a look at what resources are out there and digging into the state standards and CSTA Computer Science standards.
For the past three years, we have been working in my
district to develop a computer science program that will allow every student to
have an opportunity to learn to code and prepare themselves for a career in
computer science or that uses skills from the field of computer science.
As we roll out new resources, we are constantly looking ahead to see what is our next step. So far, this is what we have developed and what we have learned through this process.
Pre-K students have unique needs as many are not yet able to read or write. We have decided to put Lego Coding Express in our early childhood campuses and elementary schools with Pre-K students. Coding Express provides students with structured play while introducing some coding terms such as sequencing, looping, conditional coding, and cause and effect using some color-coded action bricks.
Our elementary schools are engaging students in coding during and after school. Through our partnerships with the University of Texas at Dallas and other community partners, we are able to bring graduate students and professionals to our campuses after school at no cost. During the school day, we are engaging students through interdisciplinary learning by combining computer science and math, science, social studies, and English language arts. Resources like Code.org are great since they allow us to engage our bilingual students through the various translations available. Last year, we created an Elementary Computer Science Cadre to help build this grade band of the program. This group serves as voices on their campuses to help promote this program while helping us evaluate and develop curriculum over time.
We have purchased more Sphero SPRK+s for our 13 middle
schools. Initially, this is to provide
our students with after school opportunities to learn to code or to engage
students with coding through an existing class.
Having physical resources for students who are learning to code helps
most students connect better with the concepts and see what the code does each
time it is run. Our goal is to introduce
computer science courses to our middle schools in 2020-2021. We are excited about adding a fifth year to
our vertical high school program.
Our high school program is the most developed part of our program. We offer on level, Advanced Placement, and International Baccalaureate at our various high school campuses. Our computer science teachers are a very collaborative and supportive group of teachers. Over the summer, our teachers work together to write the curriculum for these courses. We schedule three full-day pullout days to continue the momentum throughout the school year. Students have an opportunity to engage with our computing clubs that are very active in our region. These clubs compete in Java programming competitions with peers from our neighboring districts. Our three senior high campuses are known for bringing back trophies from these competitions.
Lots of work goes into building a district-wide computer science program. We encourage you to check out the work our district is doing by visiting our website at https://www.pisd.edu/computerscience.
“Teaching is not a lost art, but the regard for it is a lost tradition.” – Jacques Barzun
This past Tuesday, the daily rituals my home had fallen into over the previous two or so months were interrupted. My wife’s alarm, sounding thirty minutes earlier than usual, was the marker that for the next ten months our lives would be changing into a different, but exciting routine. It was “back to school day” for Michele, a teacher and my wife, William, a 10th grader and our eldest, and Harper, a newly christened middle schooler and our youngest. Every day most of my deliberations and actions are for and with them. Maintaining their well-being always in mind, helps keep me grounded on those individuals that should be most important in my and other educational leaders’ work, students and teachers across our communities, states, nation, and globe. I once had a supervisor who would often say, “teaching is not a fallback position, it is first choice profession;” she was, and is still to this day, 100% correct. I wanted to use my blog posting this time to remind all of our wonderful teachers that they are in a profession that deserves high-regards, support, more often than not, increased compensation, and a regular “pat on the back.”
During a training that I participated in recently, part of the introduction/icebreaker activity included each of us drawing a card with a question that we were supposed to individually meditate on and then answer out loud for the group. The question I received was, “who was the best supervisor, professor, or teacher you ever had?” After thinking about it for a while, and remembering so many people who have been extremely influential during my life, my mind drifted back and focused on 10th grade and Mr. Jack Knight. Mr. Knight was my social studies teacher, but he was so much more. He was a great teacher, a true professional educator. As I consider his class now, from an educational leader perspective, I can confidently say he was a master of maintaining classroom discipline while engaging his students in their learning. However, beyond that, Mr. Knight, who had a family of his own, also took the time to get to know and appropriately befriend and mentor a young man who greatly needed it during that time of his life; if you need a hint, that young man was me. I will not go into my personal life, but just know that his extra time, deep caring, and daily demonstration of what being a good teacher and mentor should be, has had a profound effect on me to this day and probably been more influential in my life than he will ever realize.
As teachers, you all have an immense responsibility within your position of power. You have the responsibility to teach, but more importantly you have the opportunity to make a positive difference in the life of a child which will follow them into adulthood. I hope you will never forget these facts, and it is my desire that some who are not in the classroom will soon be reminded of it.
Tuesday morning as wife and boys left our driveway to embark on this year’s adventure, I said a short prayer. That prayer, which was for safety, a “good day,” meeting new friends, and connecting with a person who really needs it, was not only for the members of my family. It was for all students and teachers; it was for you! As you progress through these first few weeks of this new year, take heart in the words of Galatians 6:9.
Go make that positive difference that I know each of you can; I wish each and every one of you a phenomenal school year!
For all of us who are living reasonably comfortable lives, we owe this largely to the march of technologies which have made our lives massively better: providing abundant food, inexpensive clothing, affordable shelter, and sanitary plumbing.
What does this have to do with artificial intelligence? Let me suggest that AI is simply the current technology for building machines that are improving our lives.
Here are three big areas in which AI is making things better, right now: medicine, energy, and food:
These are all fabulously good, amazing things that are making our world better and improving people’s lives.
Of course, there are challenges. Technology causes disruptions in work, as work previously done by people is done by machines (see Luddites, above). AI will cause the same. People will lose their jobs. New jobs will be created, but it’s not clear that the people who lose their jobs will be the ones able to fill the new jobs.
These societal challenges are best resolved with engagement in consciousness-raising and political action.
We have already seen positive change stemming from recent concerns with AI systems. Just 18 months ago, it was headline news that face-recognition systems often misidentified women and people of color.