{"id":12926,"date":"2023-09-08T15:11:23","date_gmt":"2023-09-08T15:11:23","guid":{"rendered":"https:\/\/mysourcefunding.com\/leadership\/building-skills-for-an-age-of-ai\/"},"modified":"2023-09-08T15:11:24","modified_gmt":"2023-09-08T15:11:24","slug":"building-skills-for-an-age-of-ai","status":"publish","type":"post","link":"https:\/\/mysourcefunding.com\/?p=12926","title":{"rendered":"Building Skills For An Age Of AI"},"content":{"rendered":"
\n

The world record for crossing the English Channel on foot is 14 hours and 51 minutes. President Obama does not have prime number of friends because he is not a prime number. These are a few things learned by ChatGPT users since its release nine months ago. As generative AI chatbots leverage large language models (LLMs) to predict the next word, sometimes they predict inaccurately, leading to \u201challucinations.\u201d AI hallucinations occur due to problems with training data (ChatGPT used Reddit as an input \u2013 not always the most accurate source of information) or because large language models can be biased towards generic or specific words. But although we\u2019ve now entered the age of AI, it\u2019s still far too early to attribute AI hallucinations to paranoid or depressed bots.<\/p>\n

In Douglas Adams\u2019 The Hitchhiker\u2019s Guide to the Galaxy<\/em>, Sirius Cybernetics Corporation has progressed AI from chatbots to robots and spaceships with genuine people personalities. Spaceship AI Eddie is annoyingly cheerful whenever someone walks through a door: \u201cThank you for making a simple door very happy.\u201d On the other end of the spectrum, Marvin the Paranoid Android gets everyone down: \u201cDo you want me to sit in a corner and rust, or just fall apart where I\u2019m standing?… Pardon me for breathing, which I never do anyway. So I don\u2019t know why I bother to say it. Oh God, I\u2019m so depressed.\u201d Although Marvin has a brain the size of a planet, he\u2019s assigned menial tasks and lacks the self-awareness to stop complaining for hours on end about the pain in the diodes down his left side.<\/p>\n

There are two prescient conceits at the heart of Adams\u2019 1978 radio series (later adapted into novels, television, and film). <\/em>The first is the Hitchhiker\u2019s Guide<\/em> itself, an exhaustive electronic compendium of all knowledge \u2013 including Babel fish (insert in ear for automatic translation) and the Sirius Cybernetics Corporation (\u201ca bunch of mindless jerks who\u2019ll be the first against the wall when the revolution comes\u201d) \u2013 pretty much predicting the course of the next 45 years of digital transformation. The second is Deep Thought, a supercomputer built to answer the ultimate question of \u201clife, the universe, and everything.\u201d After running for eons, Deep Thought famously produces this answer: 42. The much harder part, it turns out, is determining the question.<\/p>\n

This fairly sums up the state of generative AI: answers are readily available, but questions are everything. As poor question framing won\u2019t produce useful results, failure to ask the right questions is a much bigger barrier to our AI-enabled future than hallucinations. Insufficient human questioning-capital could end up bursting AI\u2019s bubble.<\/p>\n

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Figuring out what to ask ChatGPT may not be as complex as the ultimate question of life, the universe, and everything, but it\u2019s far from trivial. What skills do we need to ask the right questions of our new chatbot friends? For tens of millions of Americans, it could be the difference between gainful employment and being as unhappily underemployed as Marvin the Paranoid Android.<\/p>\n

What?<\/strong><\/p>\n

Knowing what to ask about requires subject matter expertise. If your job\u2019s in claims management, you need to have some understanding of how the insurance industry works and its lexicon. If you\u2019re a digital marketer, you need to know industry-standard platforms, tools, and metrics. Underscoring all this is an ability to understand the subject matter. But as specialized LLMs evolve for every industry and job function (and likely for each industry-function pairing), experience and pattern recognition will become even more important.<\/p>\n

How?<\/strong><\/p>\n

The emerging field of prompt engineering helps you figure out how to ask the right question. It can involve inputting specific instructions, context, and format of the desired output. You may need to employ techniques like chain-of-thought prompting or directional stimulus prompting. And the right question may require changing parameters like temperature and top_p. Mastering prompt engineering is like learning a foreign language to communicate with AI. (So don\u2019t expect to learn it at West Virginia\u2019s flagship university!) According to McKinsey, 7% of organizations that have adopted AI are already including prompt engineering skills in job descriptions.<\/p>\n

Why?<\/strong><\/p>\n

Knowing why you\u2019re asking means understanding the problem you\u2019re trying to solve. It can require thinking like the owner of the problem rather than a functionary \u2013 a principal instead of an agent. Much more than what or how, the \u201cwhy\u201d faculty springs from a bedrock of problem solving and critical thinking. As former IBM CEO Ginni Rommety told a Chronicle of Higher Education<\/em> audience last week, \u201cas an employer, I can give people hard skills, and in the digital world they change every three to five years. It doesn\u2019t matter that much. I really need them to understand how to work, how to think, how to problem solve.\u201d (Except it does matter. Because they wouldn\u2019t have been hired in the first place without the digital skills needed to be productive in entry-level jobs. Especially now that AI has rolled along.) But Rommety\u2019s hit the nail on the head for \u201cwhy,\u201d which involves constantly reframing questions i.e., the capability to determine the next question. And that\u2019s the kind of thinking\/solving enterprise beloved by our academic-industrial complex.<\/p>\n

When?<\/strong><\/p>\n

At what point in the problem journey should you uncork the AI genie? When is too soon \u2013 where AI could send you on a wild goose chase \u2013 and when is too late? There\u2019s judgment involved here. But as with \u201cwhat,\u201d when is mostly about experience and pattern recognition.<\/p>\n

What Next?<\/strong><\/p>\n

Likewise, figuring out what to do with AI\u2019s output \u2013 whether to copy and paste into an email or incorporate into a broader deliverable \u2013 requires critical thinking, but also reps in the role.<\/p>\n

If these are the skills needed to harness generative AI, how well is our current education system (K-12 + college) preparing graduates? Let\u2019s go with grades the system will understand.<\/p>\n

What?<\/strong> D<\/strong> Lack of integrated work experience<\/em><\/p>\n

How? F <\/strong>No training yet on prompt engineering<\/em><\/p>\n

Why? A <\/strong>[Insert school name] has worked very hard this semester\/year, and I am proud of all of his\/her accomplishments<\/em><\/p>\n

When? C <\/strong>Lack of integrated work experience<\/em><\/p>\n

What Next? B<\/strong> Lack of integrated work experience<\/em><\/p>\n

Overall C <\/strong>[Insert school name]\u2019s grades are suffering from missing assignments<\/em><\/p>\n

Within a few years, schools will get the how grade up, perhaps all the way to an A. But it\u2019s hard to see our educational institutions as currently constituted doing better than a B-. Will the problem self-correct when we get next-generation always-on AI that watches your work and presents suggestions? While what, how, and why might be off the table, when and what next would loom even larger. Either way, it\u2019s clear that equipping young Americans for AI-enhanced employment will require thinking outside the classroom box.<\/p>\n

IBM has predicted that AI won\u2019t replace people, but people who use AI will replace people who don\u2019t. As a result, keeping students penned in classrooms will impede career launch. While digital transformation has already put a premium on learning-by-doing, AI will make work experience mandatory for every learning journey. Watch as America\u2019s most innovative schools try to stabilize wobbly academic programs on a tripod consisting of these three legs:<\/p>\n

#1. Work-integrated learning<\/strong><\/p>\n

Because scaling a co-op program takes decades and isn\u2019t replicable beyond a handful of selective colleges (and certainly not for high schools), schools will need a turnkey work-integrated learning network like Riipen to connect with employers with real work problems and allow teachers to easily incorporate employer projects.<\/p>\n

#2. Internships<\/strong><\/p>\n

While about 40% of college students have internships, nearly half are unpaid. Meanwhile, formal internship programs are hard to find in higher education and as rare as hen\u2019s teeth in high school. Beyond the most selective employers leveraging summer internships as the first phase of an elaborate recruitment process, internships tend to be catch-as-catch can: informal and often relationship-based. Even when they\u2019re paid, interns are viewed as lesser employees \u2013 informality breeding a culture of not counting (as demonstrated by these Amazon and Capital One job descriptions expressly disowning internships as relevant experience). Accordingly, colleges and school districts need to formalize internship programs, probably by helping catalyze the creation of a new category of internship service providers: non-profits and for-profits that set up and operate internship programs for the benefit of employers, schools, and interns.<\/p>\n

#3. Apprenticeships<\/strong><\/p>\n

I have a few things to say about apprenticeships. There\u2019s no better way to build skills for an age of AI because apprenticeships are paid pathways to professions that equip new workers with the AI skills and experience they\u2019ll need. So figuring out how to integrate apprenticeship into curriculum (in the form of youth apprenticeships) and connect graduates to apprentice jobs should be a top priority for every school.<\/p>\n

American education has been struggling to stay above water through the first stage of digital transformation. With the onset of AI, employer expectations will shift even more dramatically. As menial tasks will no longer be fit for employee consumption, even brand new workers will be expected to be AI-productive from day one, effectively transforming entry-level jobs into mid-level jobs. The consequence for schools is stark: the work experience tripod can\u2019t be optional, adjacent, co-curricular, or extracurricular. The only way to elevate students is to make it part and parcel of core educational programs.<\/p>\n

The good news is that generative AI has the potential to help classroom education become more efficient in developing \u201cwhy\u201d skills, opening up time for integrated work experience. Nord Anglia Education just released a report on how its students are honing critical thinking skills by debating against AI. AI-powered tools like Packback (a University Ventures portfolio company) are supporting writing development through continuous moderation, feedback, revising, and rewriting while streamlining faculty grading; constant sparring on the level of an Oxbridge tutorial will do a lot to improve critical thinking and problem solving. Teachers are also beginning to use AI to develop lesson plans, presentations, and assessments. For the first time it seems possible that Baumol\u2019s cost disease \u2013 i.e., delivery of education uniquely failing to become more efficient as a result of technological development \u2013 could go the way of McGuffey Readers.<\/p>\n

But even with extra time, colleges and school districts won\u2019t solve this problem on their own. Educational institutions aren\u2019t built to connect deeply with employers. The only way to prepare the next generation for AI-enabled careers is to deliberately foster a robust ecosystem of intermediaries: work-integrated learning platforms, internship service providers, and apprenticeship intermediaries. And schools shouldn\u2019t have to go searching for them. Policymakers must recognize their importance and begin providing incentives to do this difficult work. The goal should be to have so many that all schools need to do is answer the phone (or email, or bot) and let intermediaries do the heavy lifting of incorporating work experience into secondary and postsecondary programs.<\/p>\n

Help from work experience intermediaries has the potential to open up even more classroom time: time to be human. Because until we reach Eddie- or Marvin-level AI, bot output will be devoid of self-awareness, ethics, values, and emotions. It\u2019s no accident that in Hitchhiker\u2019s Guide to the Galaxy, <\/em>the unfathomably complex next-generation computer designed by Deep Thought to determine the ultimate question turns out to be planet Earth.<\/p>\n<\/div>\n

Read the full article here<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"

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