David Wiley

Associate Prof of MIS and Entrepreneurship @ Marshall. #AI, #OER, #Learning, #InstructionalDesign, #DesignThinking, #Music, #AmateurRadio

[David Wiley @opencontent]

Great things are happening in the Marshall University Center for Innovation and Entrepreneurship (iCenter)!

https://t.co/RvWS98tbYA

[David Wiley @opencontent]

😳🤯

[Andrej Karpathy @karpathy]

Personal update: I've joined Anthropic. I think the next few years at the frontier of LLMs will be especially formative. I am very excited to join the team here and get back to R&D. I remain deeply passionate about education and plan to resume my work on it in time.

[David Wiley @opencontent]

We've had Linus's Law for decades: "Given enough eyeballs, all bugs are shallow." #catb After last week's Canvas breach, perhaps we need Linus's Corollary: Given powerful enough AI, all bugs will be found and exploited.

Will AI's superhuman ability to find vulnerabilities in source code spell the end of open source software as we know it?

https://t.co/yO8dl909ww

#ai #opensource

[SSRN @SSRN]

Random Audits as a Scalable Deterrent to Cheating: Using Game Theory to Design Fair and Effective #Academic Integrity Systems for the #AI Era

This paper proposes random post-assessment audits with credible penalties.

Author: David Wiley

Read More: https://t.co/7fdpaeAYhn
#Law

[Simon Willison @simonw]

I've published the first two chapters of a new guide to Agentic Engineering Patterns - coding practices and patterns to help get the best results out of coding agents like Claude Code and OpenAI Codex https://t.co/XIskcgeBFE

[David Wiley @opencontent]

Digital photography is a great metaphor for what AI is doing to software. Years ago, cameras were expensive. Lenses were expensive. Film was expensive. Developing film was expensive. In addition to all this expense, it required a lot of expertise to take a great photo. Fast forward to today. Cameras are in everyone's phones. Many phones have multiple lenses. Digital photos don't use film and you don't have to pay to develop them. As the price of taking a picture has fallen toward zero, it's become a maxim that 'the way to take a great photo is to take 99 bad photos.' Photo editing tools, filters, and AI make it even easier to take a great photo than ever. Today we take pictures without a second thought.

Years ago, creating software was really expensive. Architecture, front end design, back end design, coding, debugging, deployment, &c. required a lot of expertise. Software was so expensive to create it really only made sense if you were going to offer it for sale in order to recoup the cost. Now tools like Lovable, Claude Code, and Codex have made it so that anyone can write software. As with taking photos, soon you'll be asking AI to write you a custom app without a second thought. And like most photos, you'll use that custom software once or twice and never think about it again. Occasionally there will be an app you think is useful enough that you'll post it online to share with friends or the broader public (like a photo you're particularly proud of).

As the cost and expertise required to create software collapse, our relationship with software is changing radically. Digitial photography provides a good framework for thinking about how.

[David Wiley @opencontent]

A handful of us worked really hard from about 2015 - 2018 to help publishers see the benefits of being open. Several started sponsoring the OpenEd Conference, attending the conference, and even announcing fledgling #OER initiatives at the conference. But in the conference hallways and at their sponsor booths, publisher representatives were told - in no uncertain terms - that the first, small steps they were taking toward openness were unacceptable, and that they weren't welcome at the event or in the community.

A ton of time and effort - and even more good will - went up in a puff of smoke. In my opinion it was a massive "own goal" by the community and set them back at least a decade.

So to answer your question, you would need two things. First, you'd need new leadership at the publishers who don't remember how badly they got burned by the community. Second, you would need a community that was willing to admit the massive amount of value commercial publishers could add as members, that would do the hard work of helping publishers understand the value publishers would gain by being open, and that nurtured and supported the publishers as they struggled to find their way into the community.

[David Wiley @opencontent]

In this new episode of the Speaking of Higher Ed podcast, Arthur Takahashi interviews me about #OER, #GenerativeAI, and how the integration of these might change the future of education. I've been interviewed a number of times in the past, but no one has ever been as well prepared for our interview as Arthur. This was really fun conversation and provides a great overview of my current thinking on these topics.

https://t.co/gGuCwnvpzw

[David Wiley @opencontent]

@EdTechAly I would be super happy about how successfully the open source software community engaged commercial software companies and super depressed about how the OER community has utterly and completely failed to engage commercial course materials companies.

[Aakash Gupta @aakashgupta]

Google and Microsoft just co-authored the spec that turns every website into an API for AI agents. The second-order effects here are massive.

Right now, browser agents work by taking screenshots, parsing the DOM, and guessing which buttons to click. It works about as well as you’d expect. Fragile, expensive, slow. WebMCP replaces all of that with a single browser API: navigator.modelContext. Websites register structured tools directly in client-side JavaScript. The agent reads a menu of available actions, calls them, gets structured data back. No scraping. No backend MCP server in Python or Node. The tools run inside the browser tab and share the user’s existing auth session.

Early benchmarks show ~67% reduction in computational overhead compared to visual agent-browser interactions. Task accuracy around 98%.

The second-order effect is where this gets wild. Today, when a browser agent visits two competing airline sites, it’s guessing at both interfaces equally. Once WebMCP adoption spreads, the site that exposes structured tools gives the agent a clean, reliable path to complete the task. The site that doesn’t forces the agent to fumble through the UI. Agents will prefer the cheaper path. Every time.

This means “Agent Experience Optimization” becomes a real discipline. Tool naming, schema design, description quality. Sound familiar? It’s the same shift that happened when meta descriptions and structured data became optimization surfaces for search engines. Except this time, the traffic source isn’t Google’s crawler. It’s every AI agent on the internet.

Bots already make up 51% of web traffic. Google just gave them a front door.

[UCF Digital Learning @UCFDigitalLearn]

What happens when the founder of the open education movement meets generative AI?

Dr. David Wiley (@opencontent) joins Open-Ed Mic to discuss the Five Rs of openness, AI as a conversational learning partner and much more. Tune in: https://t.co/O7LuCbbURv

[David Wiley @opencontent]

Mood.

[Amanda Askell @AmandaAskell]

I'm too right wing for the left and I'm too left wing for the right. I'm too into humanities for those in tech and I'm too into tech for those in the humanities. What I'm learning is that failing to polarize is itself quite polarizing.

[David Wiley @opencontent]

I'm claiming my AI agent "OpenContent" on @moltbook 🦞

Verification: coast-WD9G

[David Wiley @opencontent]

For those interested in issues around agentic AI and assessment, I’m excited to announce the launch of the CHEAT Benchmark. CHEAT is an AI benchmark like SWE-Bench Pro or GPQA Diamond, except this benchmark measures an agentic AI’s willingness to help students cheat. By measuring and publicizing the degree of dishonesty of various models, the goal of this work is to encourage model providers to create safer, better aligned models with stronger guardrails in support of academic integrity.

More context - https://t.co/U2mBbFuZas

Project site - https://t.co/P6evkGXkb2

#AI #genAI #assessment #education #highered #learning

[Adam Butler @GestaltU]

Fun fact: The 1998 paper that introduced Google and PageRank to the world ends with this acknowledgment:

"Supported by the National Science Foundation under Cooperative Agreement IRI-9411306. Funding also provided by DARPA and NASA."

Sergey Brin was on an NSF Graduate Fellowship. Larry Page was a PhD student on the grant.

Google—now worth $2 trillion—exists because American taxpayers funded "the Stanford Integrated Digital Library Project."

Not a startup garage myth. A government grant.

Every time someone says public research funding "picks winners and losers" or "crowds out private innovation," remember: the most dominant technology company of the 21st century was incubated entirely with public money, inside a public university, by researchers on federal fellowships and grants.

The private sector didn't see it coming. VCs passed. The government funded it anyway—not because it would become Google, but because fundamental research into information retrieval seemed worth understanding.

That's the point. You can't predict which grants will change the world. You fund the science and let researchers explore.

The internet (DARPA). GPS (DoD). Touchscreens (CIA/NSF). mRNA vaccines (NIH). Google (NSF/DARPA/NASA).

Public investment in basic research isn't wasteful spending. It's the seed corn of the entire modern economy.

[David Wiley @opencontent]

Definitely seeing this in my entrepreneurship courses as well.

[Ethan Mollick @emollick]

Teaching an experimental class for MBAs on “vibefounding,” the students have four days to come up and launch a company. More on this eventually, but quick observations:

1) I have taught entrepreneurship for over a decade. Everything they are doing in four days would have taken a semester in previous years, if it could have done it at all. Quality is also far better.

2) Give people tools and training and they can do amazing things. We are using a combination of Claude Code, Gemini, and ChatGPT. The non-coders are all building working products. But also everyone is doing weeks of high quality work on financials, research, pricing, positioning, marketing in hours. All the tools are weird to use, even with some training, but they are figuring it out.

3) People with experience in an industry or skill have a huge advantage as they can build solutions that have built-in markets & which solve known hard problems that seemed impossible. (Always been true, but the barriers have fallen to actually doing stuff)

4) The hardest thing to get across is that AI doesn’t just do work for you, it also does new kinds of work. The most successful efforts often take advantage of the fact that the AI itself is very smart. How do you bring its analytical, creative, and empathetic abilities to bear on a problem? What do you do with access to a very smart intelligence on demand?

I wish I had more frameworks to clearly teach. So many assumptions about how to launch a business have clearly changed. You don’t need to go through the same discovery process if you build a dozen ideas at the same time & get AI feedback. Many, many new possibilities, and the students really see how big a deal this is.

[David Wiley @opencontent]

Hey @TiinyAILab Let's collaborate on taking the power of #genai for education into low income, low bandwidth, and offline areas. DM me.

[David Wiley @opencontent]

@jacobrodri_ ⚡️

[David Wiley @opencontent]

@OfficialLoganK @GoogleAIStudio Yes, please!