Just 30% of third-year law students think that their school is preparing them for artificial intelligence in practice, leaving 70% of soon-to-be bar candidates to learn best practices for the emerging technology on their own.
As of Sept. 1, graduates of non-ABA-accredited law schools will be allowed to sit for the bar exam in Washington state after a policy change by the state’s bar association.
Law.com reported Thursday that the change had been formally adopted by the Washington State bar Association’s Board of Governors.
The reason that I claim I am not well-suited to thrive as an instructor in the age of AI is because both AI Enthusiasts and AI Resisters put a lot of thought and energy into completely redesigning their classes in response to AI. This is the one takeaway that I don’t think the Exhausted Majority has fully accepted yet—to excel as a teacher in this AI era, you need to totally revise how you teach and how you assess what students learn in your classes.
I can say this much—whatever solution our industry comes up with, it’s likely to emerge from teaching and learning centers. Contrary to what Paul Schofield wrote in the Chronicle of Higher Education, pedagogy experts are the best hope we have to equip today’s faculty with the tools required to succeed in this uncertain educational environment. As I always tell my students, “I was trained for 7 years to become a researcher and 2 days to become a teacher.” The idea that only disciplinary experts know how to teach and have nothing to learn from so-called “nonscholars” is so laughable that one has to wonder whether an AI agent jokingly wrote that sad opinion piece to troll the whole academe.
Last week, one of the top law schools in the United States, the University of California, Berkeley School of Law, released its final policy on artificial intelligence, effective summer 2026. In the span of a breezy 1.5 pages, the school outlined the challenge AI poses to legal education and how it plans to address this problem. Despite these intentions, this AI policy is, in my estimation, the worst AI policy in higher education I have seen.
From AI Tutors to AI Study Mates— from drphilippahardman.substack.com by Dr Philippa Hardman New research reveals how AI can enable real learning — not just productivity gains
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The point isn’t that AI is inherently bad for learning — it’s that the meta-analyses showing that LLMs improve assignment and performance scores are measuring the wrong thing. They’re measuring performance with the AI present, not learning that persists once it’s gone.
. From DSC: Notice that when an AI-based learning system can remember what you’ve worked on and how you are doing — where you are struggling or doing well — it can have a positive impact on your longer-term learning. That, to me, is where long-term based learner profiles come in.
Later in the article, Dr. Hardman points out that “if we want to deliver AI tooling which supports substantive learning, we need to intentionally create a new category of AI tool for ‘learning at work’ which prioritises learning and development over productivity.” While I agree with that, I do wonder if businesses will care, so long as the work gets done and gets done well. But this calls into mind the word “experience” — something that traditionally has been hard fought to get in the corporate world. But the corporate realm often doesn’t like to pay for experience (beyond key AI-based jobs) when they perceive it’s getting too expensive. Ask all those 50 and over who had or have a target on their backs.
Easy to miss: Anthropic named the Justice Technology Association as the access-to-justice partner in the launch. The cost floor just dropped (while the product got better) for consumer legal. Law Firm 2.0 gets the headlines. A2J and direct-to-consumer is the largest white space in legal.
It has been a crazy 48 hours. We released Lavern as open source.
An agentic legal system, six months in the making, 155,000+ lines of code, 67 specialist agents, nine workflows, and at least ten things inside it that you could make as a separate product.
I was a bit anxious, like I was organising a kids’ party with balloons, unsure if anyone would come.
AUSTIN, Texas (May 19, 2026) – Deans for Impact (DFI) today released the second edition of The Science of Learning, a report translating cognitive-science research into practical implications for teaching. The updated edition includes new research on memory, attention, motivation, and learning misconceptions, offering educators a research-based foundation for understanding how to support durable student learning.
First released in 2015, The Science of Learning is DFI’s most widely-used and cited resource, with more than one million downloads. Since its publication, DFI has supported nearly 300 teacher-preparation programs to make instructional quality a priority in the way teachers are prepared, directly impacting more than 110,000 teachers over the last decade.
The second edition arrives at a moment when more than 40 states have made meaningful investments in strengthening evidence-based instruction, particularly in early literacy, mathematics, and the use of high-quality instructional materials. The science of learning supports future teachers to build a comprehensive foundation for instructional decision-making that cuts across content areas and grade levels.
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[On May 12, 2026, we introduced] 20+ new MCP connectors that link Claude to the software the legal industry already relies on, and 12 new plugins tailored to specific legal work and practice areas. And finally, we’re partnering with the Free Law Project, the Justice Technology Association, and others working to put legal help within reach of people who can’t currently access it. .
We have been building toward this moment, and now it’s finally arrived. Anthropic has formally launched ‘Claude For Legal’, a comprehensive offering that could reshape the legal tech world and places the LLM-maker at the heart of the market. (See below Artificial Lawyer interview with Mark Pike, Anthropic Associate General Counsel.)
Legal tech companies from Thomson Reuters and LexisNexis, to Harvey and Legora, are all participants in one way or another, in what is a bold strategic move that changes the legal tech market in ways that would have been unimaginable just a few years ago. (Plus, see comments from Harvey and TR below.) And of course, Freshfields has already gone all-in with Claude, while other major firms are also deeply exploring what it can do.
Claude for Legal will manifest itself across four main paths and builds on work that has already been developed:
‘New Legal Plugins: …
New MCP Connectors: …
Open-source Ecosystem: …
Plus, Free Law Project & Justice Technology Association Partnerships: …
The Justice Technology Association (JTA), a nonprofit trade group representing mission-driven companies focused on the access to justice crisis, announced today that it has joined Anthropic as a launch partner in what Anthropic is calling its first comprehensive legal vertical initiative.
The announcement comes as part of a much-broader announcement by Anthropic of its push into the legal industry, as it just released more than 20 MCP connectors to legal tech products and 12 practice-area plugins for Claude.
“Legal services are out of reach for many people and small businesses, and the gap is widening,” Anthropic said in its announcement. “We’re working with the Free Law Project, Justice Technology Association and other legal aid and public service organizations to help make legal services more affordable and available.”
That makes this the first time that a leading AI company is explicitly naming access to justice as a foundational pillar,JTA says, with Anthropic positioning the initiative as “investing in the premise that AI should expand access to justice — making legal services more affordable and available.”
Anthropic today took its biggest step yet into the legal market, releasing more than 20 new MCP connectors linking Claude to the software that law firms and legal departments run on, along with 12 new plugins tailored to specific legal practice areas.
Today’s announcement builds on the legal plugin Anthropic released in early February for Claude Cowork — the agentic desktop tool the company introduced in January as “Claude Code for the rest of your work.”
In the months since that initial release, Anthropic says legal professionals have become the most engaged Cowork users of any knowledge-work function, a statistic that likely accelerated this deeper push.
ANTHROPIC JUST OPEN-SOURCED A COMPLETE AI LEGAL SYSTEM COVERING 10 PRACTICE AREAS. 100% FREE.
80+ NAMED AGENTS handling
– contracts
– employment
– litigation
– privacy, IP
– corporate work. All of it
We welcome back Sabastian Niles, President and Chief Legal Officer at Salesforce, to discuss his recent “Open Letter to Law Firms.” As the legal industry hits a critical inflection point, Sabastian argues that the era of “AI theater” and small-scale pilots is over.
The conversation dives deep into the Innovator’s Dilemma facing law firms, the shift toward agentic AI, and how firms must reimagine their business models to remain competitive. Sabastian highlights that legal professionals are uniquely positioned to lead the charge in trusted AI transformation, provided they embrace transparency, data integration, and shared efficiency gains with their clients.
Three Realities for the Modern Legal Firm To lead in this landscape, there are three realities every firm leader must understand:
Competition is intensifying: …
Client expectations will reshape the market: Clients are no longer asking whether firms use AI. Rather, they’re expecting to see the benefits of that transformation passed directly to them. They expect more for less but are not simply seeking lower costs – they want more insight, more speed, and more value for every dollar of their budget. And law firms, which operate at the center of data, ethics, and risk, have outsized influence over the structure and deployment of trusted AI across all industries. Some clients, like Salesforce, are even creating agentic tools to improve the law firm’s experience when working with clients. …
Unified client intelligence is at the heart of legal strategy: …
Are AI First Firms a Threat To Biglaw? — from legallydisrupted.com by Zach Abramowitz and Logan Brown Episode 49 features AI first law firm founder Logan Brown
Is Big Law about to become the Yellow Pages? Hey, I didn’t say it, but ex-Cooley lawyer turned AI first law firm Logan Brown did. The question is do I agree?
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Instead of the traditional billable hour, they charge flat fees like $100 for a contract review or $50 to ask a lawyer a quick question via chat. She’s already got over 40 attorneys on the platform. And in a departure from the traditional partnership track, she actually chose to raise venture capital so she could scale the firm like a tech company and tackle the access-to-justice gap.
From DSC: LOVE to hear anything and everything regarding efforts to address the access-to-justice gap here in the United States!!! Along these lines, also see:
“Legal services are out of reach for many people and small businesses, and the gap is widening,” Anthropic said in its announcement. “We’re working with the Free Law Project, Justice Technology Association and other legal aid and public service organizations to help make legal services more affordable and available.”
That makes this the first time that a leading AI company is explicitly naming access to justice as a foundational pillar, JTA says, with Anthropic positioning the initiative as “investing in the premise that AI should expand access to justice — making legal services more affordable and available.”
What AI hallucinations in law actually are
In a legal context, AI hallucinations are one of two things. They’re either citations to cases or statutes that don’t exist, or citations to real authorities for propositions those authorities don’t actually support.
The first kind is the one making headlines. A lawyer or pro se litigant uses a general-purpose chatbot like ChatGPT, Claude, Gemini, Copilot, or Grok to help draft a brief. The model, predicting the statistically likely next word, decides a citation belongs in a particular spot, and produces one. The reporter might be real. The volume number might fall within the right range. The Bluebook formatting is often better than what most associates produce. The case itself just doesn’t exist.
The second kind is older than AI. Lawyers have always occasionally cited a case for a proposition that the case doesn’t stand for. AI has made this kind of error easier to commit and easier to catch.
A dangerous mind — from by Jordan Furlong Generative AI is a tireless genius with no boundaries. Use it carelessly, and it can usurp your voice, overwrite your ideas, and steal your originality. Make sure you safeguard your capacity to think.
Don’t let the genius do the hard work for you. The more incisive and unique your own thinking — the more you battle and struggle and eventually succeed in getting your ideas and insights out — the more you can benefit from the AI’s complementary improvements. The great irony of Gen AI is that it actually makes your own cognitive processes your most valuable asset.
So safeguard your mind. Defend your right to think as only you can. And if you don’t want AI to replace you, then don’t send it a written invitation.
The pilot phase is over. After two years of experimentation for legal departments, 2026 will be the year AI moves from “interesting tool” to “operational infrastructure,” whether they’re ready or not. We surveyed predictions from Gartner, Forrester, McKinsey, and other leading legal tech analysts to identify where expert consensus is forming. The implications for AI governance, outside counsel relationships, and regulatory compliance are significant.
Recording at LegalWeek in New York, Zach sits down with Shlomo Klapper (founder of Learned Hand) and Bridget McCormack, former Chief Justice of the Michigan Supreme Court and now CEO of the American Arbitration Association, to challenge one of the biggest double standards in legal AI: “AI for me, but not for thee.” Lawyers are now widely using AI like #Harvey and #Legora — and now more than ever #claude — but the moment it touches judges or arbitrators, support drops off.
That hesitation comes as courts are under real strain, with judges handling thousands of cases a year and only minutes to decide each one, and no realistic way to keep up. Shlomo describes Learned Hand’s “AI law clerk,” built to support judicial research, analysis, and drafting, while Bridget brings the perspective of someone who has both made decisions on the bench and has pioneered the American Arbitration Association’s AI Arbitrator, a first of its kind. The conversation moves beyond AI as an assistant and into a harder shift: AI as part of decision-making itself, and whether the system can continue to function without it.
This brings us to an admitted, glaring double standard between lawyers and judges. Lawyers are totally fine with lawyers using AI, but those same lawyers become apoplectic at the thought of judges or arbitrators using AI. It is very much “AI for me, but not for thee.” A survey last year from White & Case and Queen Mary University of London School of Law showed that nearly 90% of lawyers were deeply supportive of AI for their own research and analytics, but that support drops to just 23% when it comes to a judge or arbitrator using it to make a decision.
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Yet, despite that hullabaloo, there is a massive need for alternative forms of intelligence in our courts. Right now, the system is drowning. We have state court trial judges disposing of 2,500 cases a year, meaning they have barely half an hour to spend on a single case. We are simply not going to lawyer our way out of this 50-year backlog. If we just use humans, we have a massive demand for intelligence but a severely limited supply. AI could step in to give these judges the capacity they desperately need for the courts to actually function.
From DSC: I wish I had learned about the important financial, legal, and medical things (that are covered in the gifted article below) in high school!
How to Help Your Aging Loved Ones Plan for the Future— a gifted article from nytimes.com by Elie Levine Learn as much as you can about setting up the financial, legal and medical components of late-in-life care — and do it earlier than you might think.
Making end-of-life plans for your loved ones can feel like a burden. It is, almost by definition, complicated, and it might require having difficult conversations and sorting through a seemingly endless stream of forms and terminology. But it’s essential to your family’s well-being — and it’s worth doing earlier than you might think.
The first thing to know: There’s no one-size-fits-all approach to planning. But think of this as a starter kit that covers how to handle your parents’ current or future health challenges, and how they’ll pay for medical care. (Knowing about their medications, current finances and living situation can also help you prepare for an emergency medical situation.) Below are some of the questions to consider and discuss with your loved ones.
DC: How does this impact judges, lawyers, and law firms? What should law schools be doing?
“The accessibility of sophisticated AI tools has destroyed traditional signals of human legitimacy online. We need a new verification system immediately.”https://t.co/zwUTIrz6GR
Summary:Accessible AI has killed traditional signals of legitimacy.
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Experiments show $20 consumer tools can easily bypass verification. The solution is shifting toward contextual proof that verifies human uniqueness without exposing identity.
After Hours 1: The legal profession’s new value proposition — from jordanfurlong.substack.com by Jordan Furlong The days of selling legal tasks by the hour are ending. Lawyers’ future value lies in safeguarding clients’ legal journeys by overcoming the most challenging obstacles on the way. Part 1 of 2.
As a result, legal work is dividing into two spheres, the first larger than the second: what Gen AI can satisfactorily address, and what it can’t.
Sphere 1: Legal Production. This is all the specialized intellectual work involved in generating legal solutions: researching, issue-spotting, summarizing, synthesizing, drafting, revising, reasoning, and analyzing. This is the bulk of lawyers’ traditional activity and billed hours. In future, it will be done faster, cheaper, and increasingly better with machines — either by clients themselves, or embedded in systems and platforms that reduce the need for lawyer involvement.
Sphere 2: Legal Judgment. This is higher-value work defined by the unpredictability, complexity, and impact of its challenges. In this sphere, you’ll find hard-decision advice, guidance under uncertainty, systematic dispute avoidance, strategic counsel, critical advocacy, risk prioritization, and high-stakes accountability. It’s likely (but far from certain) that this work will remain outside the reach of Gen AI. This is the sphere that holds the potential to support a future legal profession.
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But not every legal journey is so simple or safe that the client can go it alone. Many times, Point B is more like Point F or Point R: a long and tortuous distance away. Many AI-generated maps will suggest a clear and direct route that bears little resemblance to the messy tangles of reality. On even moderately complex legal journeys, the unwelcome and the unexpected are always lurking. Something arises that was nowhere on the map, and until it gets resolved, the client can’t move any further towards their destination.
Below are some items from Jordan’s article — or by following a rabbit trail from his posting:
The emergence of AI-native law firms reveals the limits of a fixed binary that has characterized the legal market over the last year.
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The straightest path to AI law firms isn’t innovation within the legacy model, or capital investing around it, but external capital being deployed to build competitors to legacy firms. These firms use AI and narrow regulatory openings to create from scratch tech-enabled law firms.
While rates at the top continue climbing, the operational foundation of legal work is being rebuilt.
… Its pricing reflects that structure. Contract review between three and 50 pages costs $500. Short agreements are $250. Longer contracts are billed per page. Drafting from scratch is offered at a fixed fee.
There is no running clock.
The premise is straightforward. If generative AI materially reduces the time required for standardized work, the cost base changes. And when the cost base changes, pricing models eventually follow.
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Autonomous agents have already transformed engineering. Legal is next.
Agents are moving beyond assisting individuals to operating across entire workflows. This isn’t just a productivity shift, it’s an organizational one. pic.twitter.com/mMOBmJTfIA
In Episode 45 of Zach Abramowitz is Legally Disrupted, Kyle and dive into why building tech workflows and writing AI prompts should absolutely be considered billable work. We also explore why AI commoditizing the legal “grinders” and “minders” means old-school social skills are about to become your single biggest competitive advantage. Finally, Kyle goes into great detail about how exactly how he landed a top role at Legora and how others can do the same (hint: merely dropping your resume into a web portal is not enough).
A new survey of over 200 inhouse and law firm leaders provides solid evidence that while AI tools are now ‘standard’ across our sector, that trust in AI outputs fundamentally drives usage, along with ROI – and vice versa.
The data, from ALSP Factor, shows that 83% had ‘broad AI access’, which is up from 61% in 2025, and in itself is a very positive development that tells us legal AI is now becoming ubiquitous for commercial lawyers, with around 54% using such tools ‘often’.
Law Firm AI Adoption: So Many Choices — from abovethelaw.com by Stephen Embry Firms need to recognize reality, define what their legal professionals need, and then determine how to adopt and govern the use of AI tools.
It’s tough to be a law firm managing partner in the age of AI. So many choices, so little time. It’s like the proverbial kid in the candy store who has so many choices that they either can’t pick out anything or reach for too much. We see evidence of the first option in 8am’s recent outstanding Legal Industry Report, authored by Niki Black.
8am’s Legal Industry Report One thing that stood out in the report was the discrepancy between use of AI by individual legal professionals and what firms are doing when it comes to AI adoption and guidance. Almost 75% of those who responded said they were using general purpose AI tools like ChatGPT and Claude for work purposes. That’s pretty significant.
AI for good While focusing on the risks of AI going wrong, it is only fair to mention the conversations I had around using AI for good. Two in particular stand out.
The first is the news from Everlaw that its Everlaw for Good Program has, over the past year, supported more than 675 active cases across 235 organisations, and expanded its support to a growing network of non-profit organisations.
The program extends Everlaw’s technology to organisations working to advance access to justice.In a recent survey by Everlaw, 88% of legal aid professionals said they are optimistic about AI’s potential to help narrow the justice gap.
“Mission-driven organizations are increasingly handling complex investigations and litigation with limited resources,” said Joanne Sprague, head of Everlaw for Good. “Expanding access to powerful, easy-to-use technology helps level the playing field so these teams can uncover critical evidence, take on more complex matters, and yield stronger results for the communities they serve.”
The bulk of our conversation focuses on generative AI, and how Everlaw has approached it differently than much of the market. Rather than bolting on a chatbot, AJ says, Everlaw embedded AI deliberately throughout the platform — document summarization, coding suggestions, deposition analysis, fact extraction — always grounding responses in the actual documents at hand and citing sources so users can verify the work. The December launch of Deep Dive, which lets litigators pose a question and get a synthesized, cited answer drawn from an entire document corpus in about a minute, is the feature AJ calls a “new era” for discovery — one he genuinely believes represents a categorical shift.
Something Big Is Happening— from shumer.dev by Matt Shumer; see below from the BIG Questions Institute, where I got this article from
I’ve spent six years building an AI startup and investing in the space. I live in this world. And I’m writing this for the people in my life who don’t… my family, my friends, the people I care about who keep asking me “so what’s the deal with AI?” and getting an answer that doesn’t do justice to what’s actually happening. I keep giving them the polite version. The cocktail-party version. Because the honest version sounds like I’ve lost my mind. And for a while, I told myself that was a good enough reason to keep what’s truly happening to myself. But the gap between what I’ve been saying and what is actually happening has gotten far too big. The people I care about deserve to hear what is coming, even if it sounds crazy.
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They’ve now done it. And they’re moving on to everything else.
The experience that tech workers have had over the past year, of watching AI go from “helpful tool” to “does my job better than I do”, is the experience everyone else is about to have. Law, finance, medicine, accounting, consulting, writing, design, analysis, customer service.Not in ten years. The people building these systems say one to five years. Some say less. And given what I’ve seen in just the last couple of months, I think “less” is more likely.
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The models available today are unrecognizable from what existed even six months ago. The debate about whether AI is “really getting better” or “hitting a wall” — which has been going on for over a year — is over. It’s done. Anyone still making that argument either hasn’t used the current models, has an incentive to downplay what’s happening, or is evaluating based on an experience from 2024 that is no longer relevant. I don’t say that to be dismissive. I say it because the gap between public perception and current reality is now enormous, and that gap is dangerous… because it’s preventing people from preparing.
What “Something Big Is Happening” Means for Schools — from/by the BIG Questions Institute
Matt Shumer’s newsletter post Something Big is Happening has been read over 80 million times within the week when it was published, on February 9.
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Still, it’s worth reading Shumer’s post. Given the claims and warnings in Something Big Is Happening (and countless other articles), how would you truly, honestly respond to these questions:
What will the purpose of school be in 5 years?
What are we doing now that we must leave behind right away?
What can we leave behind gradually?
What does rigor look like in this AI-powered world?
Does our strategy look like making adjustments at the margins or are we preparing our students for a fundamental shift?
What is our definition of success? How do the the implications of AI and jobs (and other important forces, from geopolitical shifts and climate change, to mental health needs and shifting generational values) impact the outcomes we prioritize? What is the story of success we want to pass on to our students and wider community?
Generative AI vendor Anthropic has unveiled a legal plugin that helps customise its large language model Claude for legal tasks such as document review, sending public legal software stocks into an ensuing spin today (3 February).
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Anthropic entering the legal tech fray comes as part of the launch of a number of different plugins that help users instruct Claude on how to get work done and what tools and data to pull from. A sales plugin, for example could connect Claude to your CRM and knowledge base to help with prospect research and follow ups. The legal plug-in is described as being capable of, for example, reviewing documents, flagging risks, NDA triage, and tracking compliance. The significance is that Anthropic is shifting from model supplier to the application layer and workflow owner.
The announcement is hitting public publishing and legal software companies hard.
Two weeks after introducing a new general-purpose “agentic” work mode called Claude Cowork, Anthropic has now rolled out a legal plugin aimed squarely at the legal workflows of in-house counsel, including contract review, NDA triage, compliance checks, briefings and templated responses.
It is configurable to an organization’s own playbook and risk tolerances, and Anthropic explicitly frames it as assistance, not advice, cautioning that outputs should be reviewed by licensed attorneys.
It may sound like just another feature drop in a crowded AI market. But for legal tech, it is landing more like a tsunami than a drop. For the first time, a foundation-model company is packaging a legal workflow product directly into its platform, rather than merely supplying an API to legal-tech vendors.
What if the biggest change in education isn’t a new app… but the end of the university monopoly on credibility?
Jensen Huang has framed AI as a platform shift—an industrial revolution that turns intelligence into infrastructure. And when intelligence becomes cheap, personal, and always available, education stops being a place you go… and becomes a system that follows you. The question isn’t whether universities will disappear. The question is whether the old model—high cost, slow updates, one-size-fits-all—can survive a world where every student can have a private tutor, a lab partner, and a curriculum designer on demand.
This video explores what AI has in store for education—and why traditional universities may need to reinvent themselves fast.
In this video you’ll discover:
How AI tutors could deliver personalized learning at scale
Why credentials may shift from “degrees” to proof-of-skill portfolios
What happens when the “middle” of studying becomes automated
How universities could evolve: research hubs, networks, and high-trust credentialing
The risks: cheating, dependency, bias, and widening inequality
The 3 skills that become priceless when information is everywhere: judgment, curiosity, and responsibility
From DSC:
There appears to be another, similar video, but with a different date and length of the video. So I’m including this other recording as well here:
What if universities don’t “disappear”… but lose their monopoly on learning, credentials, and opportunity?
AI is turning education into something radically different: personal, instant, adaptive, and always available. When every student can have a 24/7 tutor, a writing coach, a coding partner, and a study plan designed specifically for them, the old model—one professor, one curriculum, one pace for everyone—starts to look outdated. And the biggest disruption isn’t the classroom. It’s the credential. Because in an AI world, proof of skill can become more valuable than a piece of paper.
This video explores the end of universities as we know them: what AI is bringing, what will break, what will survive, and what replaces the traditional path.
In this video you’ll discover:
Why AI tutoring could outperform one-size-fits-all lectures
How “degrees” may shift into skill proof: portfolios, projects, and verified competency
What happens when the “middle” of studying becomes automated
How universities may evolve: research hubs, networks, high-trust credentialing
The dark side: cheating, dependency, inequality, and biased evaluation
The new advantage: judgment, creativity, and responsibility in a world of instant answers
Penelope Adams Moon suggested that instead [of] framing a workshop around “How can we integrate AI into the work of teaching?” we should ask “Given what we know about learning, how might AI be useful?” I love that reframing, and I think it connects to the students’ requests for more AI knowhow. Students have a lot of options for learning: working with their instructor, collaborating with peers, surfing YouTube for explainer videos, university-provided social annotation platforms, and, yes, using AI as a kind of tutor. I think our job (collectively) isn’t just to teach students how to use AI (as they’re requesting) but also to help them figure out when and how AI is helpful for their learning. That’s highly dependent on the student and the learning task! I wrote about this kind of metacognition on my blog.
In the same way, when I approach any kind of educational technology, I’m looking for tools that can be responsive to my pedagogical aims. The pedagogy should drive the technology use, not the other way around.
