Graham Glass of CYPHER Learning on Five Things You Need to Create a Highly Successful Career in the…

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Graham Glass of CYPHER Learning on Five Things You Need to Create a Highly Successful Career in the AI Industry

Critical thinking. We’re living through a hot moment where AI, the new new thing, is often framed as the digital equivalent of penicillin: they say it will transform all industries and cure all ills. We see propositions brought to market that purport to be AI-powered, or AI-enhanced, but what close inspection reveals is actually just really rapid data retrieval. AI is on everyone’s lips, of course, but these are overstatements, and ultimately damaging. A seasoned critical thinker will not only distinguish genuine AI from lookalike behavior, but think more deeply about how and when to deploy AI. It’s a very important and powerful technology that changes learning, communication, and business processes in fundamental ways, but it’s not meant to be squirted all over everything, like ketchup at a picnic.

Artificial Intelligence is now the leading edge of technology, driving unprecedented advancements across sectors. From healthcare to finance, education to environment, the AI industry is witnessing a skyrocketing demand for professionals. However, the path to creating a successful career in AI is multifaceted and constantly evolving. What does it take and what does one need in order to create a highly successful career in AI?

In this interview series, we are talking to successful AI professionals, AI founders, AI CEOs, educators in the field, AI researchers, HR managers in tech companies, and anyone who holds authority in the realm of Artificial Intelligence to inspire and guide those who are eager to embark on this exciting career path.

As part of this series, we had the pleasure of interviewing Graham Glass, the co-founder and CEO of CYPHER Learning, a pioneer in the development of modern digital learning platforms.

Graham brings more than 30 years of thought leadership to the education and technology fields — an essential background for judicious application of AI in 2023. Born and educated in Britain, Graham emigrated to the U.S. in 1983. He studied, then taught, computer science and training dynamics at the University of Texas in Dallas. Lobbied by nearby technology firms to package his training curriculum for their employees, Graham founded a series of companies focused on learning and development: ObjectLesson, ObjectSpace, The Mind Electric, EDU 2.0, and, in 2006, CYPHER Learning — which is leading the revolution in AI-enhanced modern learning platforms as it serves businesses and educational institutions around the world. Graham’s written numerous books on computer programming. Today he divides his time between Texas, California, and the UK.

Thank you so much for joining us in this interview series! Before we dive in, our readers would like to learn a bit about your origin story. Can you share with us a bit about your childhood and how you grew up?

I was born in Kent, in southeast England, and grew up there and in Iran — my family moved there for part of my childhood. I got a fantastic education, particularly at Mrs. Hekmat’s School in Tehran, and was very involved in music, singing, and piano — a high point was singing a solo part in A Midsummer Night’s Dream at the Royal Opera House in London. Perhaps not the origin story you were expecting!

Can you share with us the ‘backstory” of how you decided to pursue a career path in AI?

I was drawn to computer science back when AI was still a fantastical trope in science fiction films! I studied it at the University of Southampton in England, then came to the United States for graduate work at the University of Texas. I began programming, then teaching, then found I had a facility for explaining complex things to people and went into the workplace training and education business. I founded a business (and, with my early earnings, actually built a supercomputer at home), then several more. So rather than claim I’ve been a lifelong AI careerist, it would be fairer to say I’m a career education innovator who was equipped to see the implications and potential of AI when it came along.

Can you tell our readers about the most interesting projects you are working on now?

After a lengthy, painstaking competitive review, the CYPHER Learning modern learning platform has been designated the standard e-learning tool for all pre-university schools in Qatar, public and private — which was an amazing vote of confidence. We’re working to reward their faith in us. And we’re refining CYPHER Copilot, our new AI-enhanced course-building tool for educators. It reduces a complex job that can take them hundreds of hours to ten or twelves minutes.

None of us are able to achieve success without some help along the way. Is there a particular person who you are grateful for who helped get you to where you are? Can you share a story about that?

I will always be grateful for the rigorous critical thinking skills instilled in me by Mrs. Hekmat in Tehran — and in such an exotic, eye-opening setting for a young English boy. That experience, and her wisdom, still figures in my thinking today.

As with any career path, the AI industry comes with its own set of challenges. Could you elaborate on some of the significant challenges you faced in your AI career and how you managed to overcome them?

Well, most aren’t in the rear-view mirror, they’re on our desks right now! One big challenge we face, and are still working through, is resistance in some quarters of the academic world to paradigm shifts. There’s a certain instinct to defend the status quo that can make AI a harder case to press, even when its value and efficiencies are self-evident.

Not unrelated: a non-trivial number of the creative class — journalists, writers, graphic artists — express existential fears about AI; some think it’s going to run them out of their jobs. We have to be empathetic while explaining that will rarely be the case, and is certainly never the intent.

And, finally, we face the same challenges regarding data verification familiar to everyone working in the digital information sphere. The most important question we can ask today about things we find online is: How do you know? What’s the provenance of this data? A language learning model (LLM) that applies its deep learning algorithm to fake data may be impressive technology, but unhelpful technology if it synthesizes glib, grammatically correct … junk. We’re solving those challenges now, and what I can say is, the solution has a journalistic ring to it: a good reporter gets confirmation from multiple sources before running with a story.

Ok, let’s now move to the main part of our interview about AI. What are the 3 things that most excite you about the AI industry now? Why?

Looking at the entire industry, I’d say the three most exciting things are:

  • The speed of recent advances. Open AI launched GPT-1 in mid-2018, and GPT-4 came just five years later. Each iteration is exponentially more thorough than the last: 117 million parameters for GPT-1, reportedly 1.75 trillion for GPT-4. That rate of progress makes Moore’s Law look plodding.
  • Public access at scale to ChatGPT, Google Bard, and many more like them. The first public version of ChatGPT had 100 million users within two months of release; hitting that milestone took Instagram two and a half years. Most have run prompts past AI chatbots by now and weighed the results. This demystifies the technology, models its strengths and imperfections, and casts it, properly, as more of a virtual assistant and helpmate — not a sinister threat. This mass socialization on each individual user’s terms is much healthier than some sort of grand global rollout date. (The technology’s too multilateral for that anyway.)
  • Unanticipated developments! In the era of the connected PC we were continually surprised by innovations: brand new product categories, new experience design conventions. And AI evolution and adoption are happening far faster. Let’s see what happens.

What are the 3 things that concern you about the AI industry? Why? What should be done to address and alleviate those concerns?

  • The use of AI to deceive. There’s no deliberately deceptive iota of code in AI, but it can certainly be made an accessory to deception. Already deepfakes and misleading mashups are flooding social media; platform providers and users ought to play greater screening-and-flagging roles. (We hear frequently that students are using ChatGPT to dash off their essay assignments; what are instructors meant to do about it? One answer: stop assigning make-work essays and grade students more meaningfully.)
  • Apocalyptic rhetoric. Too many people, some of them policy influencers, base faulty views of AI on 2001: A Space Odyssey, where HAL9000 goes haywire and locks astronaut Dave out of the spaceship. That’s not today’s reality. The more transparency we can bring to the public square, the better off we all are.
  • A constant, broad-based concern: cybersecurity. Malicious actors are using AI in their attack strategies; their targets have to fight fire with fire. Impressive AI-powered cyber defense solutions are available, but the adoption rate could be better. We’ve got to raise consciousness and instill more urgency among those with assets at risk.

For a young person who would like to eventually make a career in AI, which skills and subjects do they need to learn?

Learning to code is important — I still contribute code to CYPHER Learning software. A working knowledge of linguistics will be very helpful. I place high value on knowing the history of computer science and the technology adoption curve — how and why some innovations triumph beyond the Gartner Hype Cycle while others thrash around in the Trough of Disillusionment. And if you’re a musician, that tells me your curiosities and passions extend beyond tech to the world in which we deploy tech — so talk to me.

As you know, there are not that many women in the AI industry. Can you advise what is needed to engage more women in the AI industry?

More role models, and more confidence among the considerers of a warm, supportive welcome and a positive work culture. Thankfully the stereotype of the intimidating white male Silicon Valley tech-bro bully is out of style; it cost the technology industry so much talent and diversity, and made it look out of sync with the big, broad culture. But even today about 92% of code-writers are still men. We should be paying more attention to thought leaders like Fei-Fei Li, who co-directs Human-Centered AI Institute at Stanford, just up the road from me, and Kimberley Bryant, whose nonprofit. Black Girls Code, is out to teach one million Black girls to code by 2040. The more visibility such women achieve, the more inviting our industry looks, I believe. And goodness knows more diverse perspectives on the creation-and-innovation side are a prerequisite to global acceptance of AI.

Ethical AI development is a pressing concern in the industry. How do you approach the ethical implications of AI, and what steps do you believe individuals and organizations should take to ensure responsible and fair AI practices?

AI is a fundamentally benign but malleable technology that must be handled judiciously. If users are nervous about security, privacy, or veracity, AI won’t be embraced — so it’s on the industry to inspire confidence. We have to be open to thinking about what disclosure policies and practices might help, such as sharing the procedures we use during internet scans to filter out misinformation — something CYPHER Learning is doing right now, with multiple AIs cross-checking one another before delivering synthesized information to a user.

Ok, here is the main question of our interview. Can you please share the “Five Things You Need To Create A Highly Successful Career In The AI Industry”?

1 . Critical thinking. We’re living through a hot moment where AI, the new new thing, is often framed as the digital equivalent of penicillin: they say it will transform all industries and cure all ills. We see propositions brought to market that purport to be AI-powered, or AI-enhanced, but what close inspection reveals is actually just really rapid data retrieval. AI is on everyone’s lips, of course, but these are overstatements, and ultimately damaging. A seasoned critical thinker will not only distinguish genuine AI from lookalike behavior, but think more deeply about how and when to deploy AI. It’s a very important and powerful technology that changes learning, communication, and business processes in fundamental ways, but it’s not meant to be squirted all over everything, like ketchup at a picnic.

2 . A people-first mindset. AI is not a license to extract human judgment from important business systems or communications, and I disagree with those who imply otherwise. I see business-to-business advertisements offering per diem chatbots to write your press releases and internal memos. But AI at its best is not a replacement for the creative class — it’s there to make people more influential and effective. Look at what CYPHER Copilot does in the classroom, for example: when it generates multi-module courses and quizzes in minutes instead of hours, it relieves teachers of rote, repetitive, perhaps tedious work, but it scarcely replaces teachers — any more than trigonometry calculators replace mathematicians. I like to say we can delegate perhaps 80% of that spadework to AI, but people will contribute the other 20% — as reviewers, editors, mentors, they’re irreplaceable. AI done right elevates people. Those who get that will thrive in this new sphere.

3 . A wide-angle lens. In other words, a knack for seeing the context and implications of AI implementations. If we see AI-powered autonomous vehicles eventually supplant some human drivers, for example, what is the next move for those drivers — and how do they anticipate and help manage big workforce shifts like that? It must be said that in prior chapters of our digital transformation, tech champions have rarely achieved this wide-angle view; virtually all of the PC’s eras biggest innovations, from eBay to Pirate Bay, were surprises, and I don’t know any social media innovators in the 2000s who forecast the disinformation problems social media has in 2023. Now we must be inspired to think bigger and do better. Those who can envision the economic, societal, and political ramifications of AI, positive and otherwise, are more likely to emerge as thought leaders.

4 . Diplomacy. Government efforts to regulate AI are inevitable worldwide. They’re already underway, especially in the European Union, and many legislators and policy architects are starting in a state of alarm. These are opportunities for technologists and politicians to collaborate on operating and usage frameworks for AI that build public confidence. The AI revolution is building as the other huge challenge of the internet era, protecting privacy and security, reaches critical mass. Together they’ll dominate the 2020s. I and others like me are staunch, if measured, AI advocates, but that doesn’t make going full bulldozer on AI’s behalf a winning strategy. Diplomatic, listening, and negotiating skills are going to be very important for those seeking to lead this business sector.

5 . Children. You certainly need not have children of your own to care about them, but I think it’s important that we build this new world with the welfare of children in mind. I’m raising two young sons. They are my first priority. When I strategize the harnessing of AI at CYPHER Learning, I am always thinking: what are the upsides for our kids? What might be the risks and challenges? It keeps me centered, absolutely, but I hope the entire sector thinks that way. Blend that perspective to the one you get from hustling to hit quarterly numbers, and I think you can be the sort of leader the AI field needs more of.

Continuous learning and upskilling are vital in a dynamic field like AI. How do you approach ongoing education and stay up-to-date with the latest advancements in the AI industry? What advice do you have for those looking to grow their careers in AI?

We all read the industry briefs. I don’t think all of us are also reading The New Yorker, or The Economist, or even The Hollywood Reporter — but we should.

My advice would be to adopt the da Vinci playbook. Leonardo was a scientist and inventor but also, obviously, a painter, architect, anatomist, writer, sculptor — the very model of a multidisciplinary Renaissance man. He was passionate about so many things. If we’re going to leverage AI to guide transformation of society at large, we too should be invested in society at large.

That means enthusiasm for arts and culture, great writing, geopolitics, of course — but also business sectors AI will change, from transportation to energy to health care. One of my pastimes is to take subjects I love and want to know more about — from giraffes to Thunderbirds, the British sci-fi TV show from the 1960s starring amazing flying vehicles and marionettes (Google it!) — and use CYPHER Learning’s AI-powered course-building tools to create learning programs for myself on those topics. The lesson, of course, is that it’s important to be passionate about AI, but for most people AI is a means to an end.

So: cultivating diverse interests is to me essential. It’s not a fail if you don’t hit da Vinci’s level, but we can all be well-rounded.

What is your favorite “Life Lesson Quote”? Can you share a story of how that had relevance to your own life?

I’ll take you straight back to da Vinci: “Realize that everything connects to everything else.” Technology innovators don’t operate in a societal silo. It’s a cardinal principle behind my approach to AI.

You are a person of great influence. If you could start a movement that would bring the most amount of good to the most amount of people, what would that be? You never know what your idea can trigger. 🙂

Speaking of framing AI as a means to an end: AI-powered distance learning technologies have enormous potential for multiplying great teachers’ reach and influence, and exporting their ideas across borders and great distances. In earlier times a student had to travel to the Sorbonne, or Oxford, or Cal Tech to gain access to the best and brightest in their fields, and such access was the province of the privileged. Now equal access is, in principle, within our reach, and AI can assist with lesson plans, translations, evaluations, and pointing students toward further study. And what’s possible at the university level is equally so for young learners: it’s within our grasp to create a grand, globally connected schoolroom that literally elevates billions. I’d love to help convene academics, governments, businesses, and AI thinkers to help make these things happen.

How can our readers further follow your work online?

I take part in webinars and virtual panels and post before-and-after notices regularly on LinkedIn. I seek feedback and advice from those who look in. I’m happy to have you do the same at I’m also on X, formerly Twitter: @grahamglass.

This was very inspiring. Thank you so much for joining us!

Thank you very much. I’m pleased you are as interested as I am in this very important subject. I appreciate this time.

Graham Glass of CYPHER Learning on Five Things You Need to Create a Highly Successful Career in the… was originally published in Authority Magazine on Medium, where people are continuing the conversation by highlighting and responding to this story.