From DSC: Last Thursday, I presented at the Educational Technology Organization of Michigan’s Spring 2024 Retreat. I wanted to pass along my slides to you all, in case they are helpful to you.
AI Policy 101: a Beginners’ Framework — from drphilippahardman.substack.com by Dr. Philippa Hardman How to make a case for AI experimentation & testing in learning & development
The role of learning & development
Given these risks, what can L&D professionals do to ensure generative AI contributes to effective learning? The solution lies in embracing the role of trusted learning advisors, guiding the use of AI tools in a way that prioritizes achieving learning outcomes over only speed. Here are three key steps to achieve this:
1. Playtest and Learn About AI… 2. Set the Direction for AI to Be Learner-Centered…
3. Become Trusted Learning Advisors…
In the last year, AI has become even more intertwined with our education system. More teachers, parents, and students are aware of it and have used it themselves on a regular basis. It is all over our education system today.
While negative views of AI have crept up over the last year, students, teachers, and parents feel very positive about it in general. On balance they see positive uses for the technology in school, especially if they have used it themselves.
Most K-12 teachers, parents, and students don’t think their school is doing much about AI, despite its widespread use. Most say their school has no policy on it, is doing nothing to offer desired teacher training, and isn’t meeting the demand of students who’d like a career in a job that will need AI.
The AI vacuum in school policy means it is currently used “unauthorized,” while instead people want policies that encourage AI. Kids, parents, and teachers are figuring it out on their own/without express permission, whereas all stakeholders would rather have a policy that explicitly encourages AI from a thoughtful foundation.
There is much discourse about the rise and prevalence of AI in education and beyond. These debates often lack the perspectives of key stakeholders – parents, students and teachers.
In 2023, the Walton Family Foundation commissioned the first national survey of teacher and student attitudes toward ChatGPT. The findings showed that educators and students embrace innovation and are optimistic that AI can meaningfully support traditional instruction.
A new survey conducted May 7-15, 2024, showed that knowledge of and support for AI in education is growing among parents, students and teachers. More than 80% of each group says it has had a positive impact on education.
AI’s New Conversation Skills Eyed for Education — from insidehighered.com by Lauren Coffey The latest ChatGPT’s more human-like verbal communication has professors pondering personalized learning, on-demand tutoring and more classroom applications.
ChatGPT’s newest version, GPT-4o ( the “o” standing for “omni,” meaning “all”), has a more realistic voice and quicker verbal response time, both aiming to sound more human. The version, which should be available to free ChatGPT users in coming weeks—a change also hailed by educators—allows people to interrupt it while it speaks, simulates more emotions with its voice and translates languages in real time. It also can understand instructions in text and images and has improved video capabilities.
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Ajjan said she immediately thought the new vocal and video capabilities could allow GPT to serve as a personalized tutor. Personalized learning has been a focus for educators grappling with the looming enrollment cliff and for those pushing for student success.
There’s also the potential for role playing, according to Ajjan. She pointed to mock interviews students could do to prepare for job interviews, or, for example, using GPT to play the role of a buyer to help prepare students in an economics course.
Hello GPT-4o — from openai.com We’re announcing GPT-4o, our new flagship model that can reason across audio, vision, and text in real time.
GPT-4o (“o” for “omni”) is a step towards much more natural human-computer interaction—it accepts as input any combination of text, audio, image, and video and generates any combination of text, audio, and image outputs. It can respond to audio inputs in as little as 232 milliseconds, with an average of 320 milliseconds, which is similar to human response time in a conversation. It matches GPT-4 Turbo performance on text in English and code, with significant improvement on text in non-English languages, while also being much faster and 50% cheaper in the API. GPT-4o is especially better at vision and audio understanding compared to existing models.
Providing inflection, emotions, and a human-like voice
Understanding what the camera is looking at and integrating it into the AI’s responses
Providing customer service
With GPT-4o, we trained a single new model end-to-end across text, vision, and audio, meaning that all inputs and outputs are processed by the same neural network. Because GPT-4o is our first model combining all of these modalities, we are still just scratching the surface of exploring what the model can do and its limitations.
This demo is insane.
A student shares their iPad screen with the new ChatGPT + GPT-4o, and the AI speaks with them and helps them learn in *realtime*.
Imagine giving this to every student in the world.
OpenAI rolls out Memory feature for ChatGPT
OpenAI has introduced a cool update for ChatGPT (rolling out to paid and free users – but not in the EU or Korea), enabling the AI to remember user-specific details across sessions. This memory feature enhances personalization and efficiency, making your interactions with ChatGPT more relevant and engaging.
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Key Features
Automatic Memory Tracking
ChatGPT now automatically records information from your interactions such as preferences, interests, and plans. This allows the AI to refine its responses over time, making each conversation increasingly tailored to you.
Enhanced Personalization
The more you interact with ChatGPT, the better it understands your needs and adapts its responses accordingly. This personalization improves the relevance and efficiency of your interactions, whether you’re asking for daily tasks or discussing complex topics.
Memory Management Options
You have full control over this feature. You can view what information is stored, toggle the memory on or off, and delete specific data or all memory entries, ensuring your privacy and preferences are respected.
Memory is now available to all ChatGPT Plus users. Using Memory is easy: just start a new chat and tell ChatGPT anything you’d like it to remember.
Memory can be turned on or off in settings and is not currently available in Europe or Korea. Team, Enterprise, and GPTs to come. pic.twitter.com/mlt9vyYeMK
From DSC: The ability of AI-based applications to remember things about us will have major and positive ramifications for us when we think about learning-related applications of AI.
The theme of the day was Human Connection V Innovative Technology. I see this a lot at conferences, setting up the human connection (social) against the machine (AI). I think this is ALL wrong. It is, and has always been a dialectic, human connection (social) PLUS the machine. Everyone had a smartphone, most use it for work, comms and social media. The binary between human and tech has long disappeared.
Galaxy AI introduces meaningful intelligence aimed at enhancing every part of life, especially the phone’s most fundamental role: communication. When you need to defy language barriers, Galaxy S24 makes it easier than ever. Chat with another student or colleague from abroad. Book a reservation while on vacation in another country. It’s all possible with Live Translate,2 two-way, real-time voice and text translations of phone calls within the native app. No third-party apps are required, and on-device AI keeps conversations completely private.
With Interpreter, live conversations can be instantly translated on a split-screen view so people standing opposite each other can read a text transcription of what the other person has said. It even works without cellular data or Wi-Fi.
Galaxy S24 — from theneurondaily.com by Noah Edelman & Pete Huang
Samsung just announced the first truly AI-powered smartphone: the Galaxy S24.
For us AI power users, the features aren’t exactly new, but it’s the first time we’ve seen them packaged up into a smartphone (Siri doesn’t count, sorry).
But a few applications of machine learning stood out as genuinely helpful or surprising — here are a few examples of AI that might actually do some good.
The whole idea that AI might not be a total red flag occurred to me when I chatted with Whispp at a press event. This small team is working on voicing the voiceless, meaning people who have trouble speaking normally due to a condition or illness.
The Emerging Role of Smart TVs Boothe and Comiskey claim that our TVs will become even smarter and better connected to the web and the internet. Our TVs will become an intelligent center for a variety of applications powered through our smartphone. TVs will be able to direct things like appliances and security cameras. Perhaps even more importantly, our TVs can become e-commerce centers, allowing us to speak with them and conduct business.
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This increased TV capability means that the TV could become a more dominant mode of working and computing for lawyers. As TVs become more integrated with the internet and capable of functioning as communication hubs, they could potentially replace traditional computing devices in legal settings. With features like voice control and pattern recognition, TVs could serve as efficient tools for such things as document preparation and client meetings.
From DSC: Now imagine the power of voice-enabled chatbots and the like. We could be videoconferencing (or holograming) with clients, and be able to access information at the same time. Language translation — like that in the Timekettle product — will be built in.
As we step into 2024, the legal industry continues to be reshaped by technological advancements. This year promises to bring new developments that could revolutionize how legal professionals work and interact with clients. Here are key predictions for legal tech in 2024:
Last Friday was Legaltech Week’s year-end show, in which our panel of journalists and bloggers picked the year’s top stories in legal tech and innovation.
So what were the top stories? Well, if you missed it, no worries. Here’s the video:
During lockdown, we were forced to start producing videos for Moocs remotely. This was quite successful, and we continue to use these techniques whenever a contributor can’t come to the studio. The same principles can be used by anyone who doesn’t have access to a media production team. Here are our tips on producing educational videos on a budget.
Programmable medicines. AI tools for kids. We asked
over 40 partners across a16z to preview one big idea
they believe will drive innovation in 2024.
Narrowly Tailored, Purpose-Built AI In 2024, I predict we’ll see narrower AI solutions. While ChatGPT may be a great general AI assistant, it’s unlikely to “win” for every task. I expect we’ll see an AI platform purpose-built for researchers, a writing generation tool targeted for journalists, and a rendering platform specifically for designers, to give just a few examples.
Over the longer term, I think the products people use on an everyday basis will be tailored to their use cases — whether this is a proprietary underlying model or a special workflow built around it. These companies will have the chance to “own” the data and workflow for a new era of technology; they’ll do this by nailing one category, then expanding. For the initial product, the narrower the better.
— via Olivia Moore, who focuses on marketplace startups
So asks a recent study by two academics from Stanford Law School, David Freeman Engstrom and Nora Freeman Engstrom, on the potential impact of AI on the civil litigation landscape in the US.
It is against this landscape, the study observes, that champions of legal tech have suggested that there is an opportunity for legal tech to “democratise” litigation and put litigation’s “haves” and “have nots” on a more equal footing, by arming smaller firms and sole practitioners with the tools necessary to do battle against their better resourced opponents, and cutting the cost of legal services, putting lawyers within reach of a wider swathe of people.
But is this a real opportunity, and will AI be key to its realisation?
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However, while AI may reduce the justice gap between the “haves” and “have-nots” of litigation, it could also exacerbate existing inequalities.
From DSC: While this article approaches things from the lawyer’s viewpoint, I’d like to see this question and the use of AI from the common man’s/woman’s viewpoint. Why? In order to provide FAR GREATER access to justice (#A2J) for those who can’t afford a lawyer as they head into the civil law courtrooms.
Should I take my case to court? Do I have a chance to win this case? If so, how?
What forms do I need to complete if I’m going to go to court?
When and how do I address the judge?
What does my landlord have to do?
How do I prevent myself from falling into a debt-collection mess and/or what options do I have to get out of this mess?
Are there any lawyers in my area who would take my case on a pro bono basis?
…and judges and lawyers — as well as former litigants — could add many more questions (and answers) to this list
Bottom line: It is my hope that technology can help increase access to justice.
A number of products are already under development, or have been launched. One example is a project that Norton Rose Fulbright is working on, together with not-for-profit legal service Justice Connect. The scope is to develop an automated natural language processing AI model that seeks to interpret the ‘everyday’ language used by clients in order to identify the client’s legal issues and correctly diagnose their legal problem. This tool is aimed at addressing the struggles that individuals often face in deciphering legal jargon and understanding the nature of their legal issue and the type of lawyer, or legal support, they need to resolve that problem.
From DSC: As I’ve long stated on the Learning from the Living [Class]Room vision, we are heading toward a new AI-empowered learning platform — where humans play a critically important role in making this new learning ecosystem work.
Along these lines, I ran into this site out on X/Twitter. We’ll see how this unfolds, but it will be an interesting space to watch.
From DSC: This future learning platform will also focus on developing skills and competencies. Along those lines, see:
Scale for Skills-First— from the-job.beehiiv.com by Paul Fain An ed-tech giant’s ambitious moves into digital credentialing and learner records.
A Digital Canvas for Skills
Instructure was a player in the skills and credentials space before its recent acquisition of Parchment, a digital transcript company. But that $800M move made many observers wonder if Instructure can develop digital records of skills that learners, colleges, and employers might actually use broadly.
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Ultimately, he says, the CLR approach will allow students to bring these various learning types into a coherent format for employers.
Instructure seeks a leadership role in working with other organizations to establish common standards for credentials and learner records, to help create consistency. The company collaborates closely with 1EdTech. And last month it helped launch the 1EdTech TrustEd Microcredential Coalition, which aims to increase quality and trust in digital credentials.
It’s an era many instructors would like to put behind them: black boxes on Zoom screens, muffled discussions behind masks, students struggling to stay engaged. But how much more challenging would teaching during the pandemic have been if colleges did not have experts on staff to help with the transition? On many campuses, teaching-center directors, instructional designers, educational technologists, and others worked alongside professors to explore learning-management systems, master video technology, and rethink what and how they teach.
A new book out this month, Higher Education Beyond Covid: New Teaching Paradigms and Promise, explores this period through the stories of campus teaching and learning centers. Their experiences reflect successes and failures, and what higher education could learn as it plans for the future.
As usual, our readers were full of suggestions. Kathryn Schild, the lead instructional designer in faculty development and instructional support at the University of Alaska at Anchorage, shared a guide she’s compiled on holding asynchronous discussions, which includes a section on difficult topics.
In an email, Schild also pulled out a few ideas she thought were particularly relevant to Le’s question, including:
Set the ground rules as a class. One way to do this is to share your draft rules in a collaborative document and ask students to annotate it and add suggestions.
Plan to hold fewer difficult discussions than in a face-to-face class, and work on quality over quantity. This could include multiweek discussions, where you spiral through the same issue with fresh perspectives as the class learns new approaches.
Start with relationship-building interactions in the first few weeks, such as introductions, low-stakes group assignments, or peer feedback, etc.
Forty-one states and the District of Columbia are suing Meta, alleging that the tech giant harms children by building addictive features into Instagram and Facebook. Tuesday’s legal actions represent the most significant effort by state enforcers to rein in the impact of social media on children’s mental health.
