The widespread adoption and use of generative AI means that folks no longer need to be an expert in "hard" skills such as statistics & probability, calculus, or linear algebra to get value from using Generative AI. Instead, the need to use soft skills such as communication, curiosity, problem solving, and adaptability is becoming more important. In this episode of AI Today hosts Kathleen Walch and Ron Schmelzer discuss the growing need for critical thinking skills.

What it means to have critical thinking

Critical thinking is the skill of obtaining a solid, reliable, and as accurate an understanding of information as possible, and then using that understanding to make sound decisions. This involves carefully examining information, questioning assumptions, and ensuring that conclusions are supported by strong evidence. In this episode we discuss why this is important when using and interacting with AI models.

Improving your skills

When it comes to soft skills, it's a lifelong learning journey. In this episode we discuss how you can continue to improve on these soft skills. Approaching AI interactions with a healthy dose of skepticism is essential. Question your assumptions and evaluate whether the information processed by AI systems makes sense. Identify the assumptions being made and seek evidence to support or refute them.

Show Notes:

• Free Intro to CPMAI course





• CPMAI Certification





• Subscribe to Cognilytica newsletter on LinkedIn





• Is Critical Thinking A Superpower In The AI Era?





• Basic Elements of Critical Thinking

 

Download audio: https://media.blubrry.com/aitoday/content.blubrry.com/aitoday/AIToday-Episode-443-The-Necessary-Soft-Skills-for-AI--Critical-Thinking.mp3

First we dive into some exciting news of actual innovation: ultrasonic extraction for cold brew coffee. Then offer a live react to OpenAI’s new product GPT-4o, which is its new flagship model in the form of a voice assistant, and jump from there to talk more deeply about the problems with AI companions via a tech column in the NYTimes. ••• Scientists Use Ultrasound to Make Cold Brew Coffee in 3 Minutes Instead of 24 Hours https://www.404media.co/scientists-use-ultrasound-to-make-cold-brew-coffee-in-3-minutes-instead-of-24-hours/ ••• Hello GPT-4o https://openai.com/index/hello-gpt-4o/ ••• Meet My A.I. Friends https://www.nytimes.com/2024/05/09/technology/meet-my-ai-friends.html Subscribe to hear more analysis and commentary in our premium episodes every week! https://www.patreon.com/thismachinekills Hosted by Jathan Sadowski (www.twitter.com/jathansadowski) and Edward Ongweso Jr. (www.twitter.com/bigblackjacobin). Production / Music by Jereme Brown (www.twitter.com/braunestahl)



Download audio: https://feeds.soundcloud.com/stream/1822962681-thismachinekillspod-340-with-ai-friends-like-these-who-needs-society.mp3

Welcome to episode #932 of Six Pixels of Separation – The ThinkersOne Podcast.

Here it is: Six Pixels of Separation – The ThinkersOne Podcast – Episode #932. Nicholas Mattei is an Associate Professor of Computer Science at Tulane University. Nick has dedicated his career to exploring the theory and practice of artificial intelligence, with a focus on decision-making systems for both autonomous agents and humans. He’s been into AI since he was young, influenced by his mother (a program coordinator at a science center, and his father, a professor). His early fascination with computers and programming laid the foundation for a career that has spanned prestigious institutions and cutting-edge projects. Before joining Tulane University, Nick worked as a Research Staff Member at the IBM TJ Watson Research Laboratory, where he tackled complex problems in question answering, natural language inference, decision making, and the ethical implications of AI on society. Prior to his time at IBM, he contributed to the AI & Algorithmic Decision Theory Group at Data61 in Australia. His work there and his involvement in organizing workshops on computational social choice highlight his commitment to advancing AI research. He also spent time at NASA in engineering where he was responsible for the design and implementation of control systems software for multiple small satellites. All cool stuff. At Tulane, Nick is not only advancing AI research but also emphasizing the importance of interdisciplinary collaboration. He works closely with the law school and sociology departments to study the societal impacts of AI. His leadership at the Tulane Center of Excellence for Community-Engaged AI demonstrates his dedication to ensuring that technological advancements benefit the wider community. Nick is passionate about education and mentorship, continually striving to inspire the next generation of AI researchers. His ability to bridge the gap between theoretical AI and practical applications makes him a valuable asset to both the academic and broader communities… and business thinkers like you. If you’re trying to understand the distinctions between traditional coding and AI, the nuances of machine learning, and the evolving landscape of AI technologies, this one is for you. Nick reflects on the challenges and opportunities presented by Generative AI, as well as his thoughts on the ethical deployment of AI systems, offering a nuanced perspective on the future of technology. His pragmatic approach to AI, coupled with his optimism about its potential to create value, provides a balanced view that is both insightful and thought-provoking at a time when we need it most. Enjoy the conversation…

• Running time: 1:06:08.
• Hello from beautiful Montreal.
• Subscribe over at Apple Podcasts.
• Please visit and leave comments on the blog – Six Pixels of Separation.
• Feel free to connect to me directly on Facebook here: Mitch Joel on Facebook.
• Check out ThinkersOne.
• or you can connect on LinkedIn.
• …or on Twitter.
• Here is my conversation with Nicholas Mattei.
• Tulane University.
• Tulane Center of Excellence for Community-Engaged AI.
• Follow Nick on LinkedIn.
• Follow Nick on X.
• This week’s music: David Usher ‘St. Lawrence River’.

Takeaways

• AI involves making computers appear intelligent and capable of simulating human intelligence.
• Generative AI, such as ChatGPT, uses large language models to generate text based on patterns in data.
• The transformer architecture has revolutionized AI by enabling more efficient training and generation of text.
• Generative AI has the potential to create intimate and personalized experiences, but it lacks true understanding and creativity.
• The impact of AI on work and employment is significant, with repetitive tasks being the most vulnerable to automation. 
• The creative class may face challenges as AI becomes more capable of performing creative tasks.
• Training and education are crucial to adapt to the changing nature of work.
• Responsible deployment of AI is essential to avoid negative consequences.
• The concept of AGI and its potential risks are subjects of debate.
• Alignment, or ensuring AI works in accordance with human values, is a critical consideration in AI development.

Chapters:

• 00:00 – Introduction and Background
• 06:31 – Defining AI and Coding
• 10:38 – Delineation Between AI and Generative AI
• 14:40 – AI’s Ability to Reason and Explain
• 19:30 – The Power and Limitations of Generative AI
• 23:47 – The Significance of the Transformer Architecture
• 32:42 – The Intimacy of Chatbots and the Future of AI
• 39:26 – OpenAI’s Approach to Generative AI
• 41:22 – The Impact of AI on Work and Employment
• 42:17 – The Value of AI and the Potential for Extremism
• 44:04 – The Impact of AI on the Creative Class
• 45:02 – The Historical Context of AI Displacing Jobs
• 46:14 – The Evolution of Work and the Need for Training
• 47:23 – The Creation of Value and the Changing Nature of Work
• 48:44 – The Challenges of Responsible Deployment of AI
• 49:50 – The Debate Around AGI and its Potential Risks
• 1:01:04 – The Importance of Alignment in AI
• 1:04:08 – The Power of Model-Free AI and Changing Perspectives

Download the Podcast here: Six Pixels of Separation – The ThinkersOne Podcast – Episode #932.

Before you go… ThinkersOne  is a new way for organizations to buy bite-sized and personalized thought leadership video content (live and recorded) from the best Thinkers in the world. If you’re looking to add excitement  and big smarts to your meetings, corporate events, company off-sites, “lunch & learns” and beyond, check it out.

Regarding the supposed furor over #WokeGemini…

If we saw generative AI as a creative tool, then I’d say imagining the founding of America with women & Black people at the table and the Catholic Church headed by Black women and Native Americans is a proper revision of history the way it should have been.

The reaction to #WokeGemini says more about society than the tool itself; that’s what fascinates me about AI: its reflections. Right-wing columnists fear the anti-white machine programmed by commisars of what we used to call political correctness.

And the extremist Murdoch media and pols hunt for enemies: technologists who dare to recognize “white privilege.” Their strategy of projection works in media today: calling anti-racism racism to deflect from their deep racism, just as calling Biden old and doddering deflects from the truly doddering Trump. In today’s credulous media, it works.

Ultimately, this little episode shows the folly of “guardrails” in AI, for a tool can be made to do anything and what it is proscribed from doing — and reaction to that — can be more revealing and risky than the tool alone. It is like telling Gutenberg what movable type must never say. The Church tried to do just that with his successors as, at first, the technology was held responsible for what it produced: printers were beheaded and behanded for what their machines produced. Then booksellers were held liable and controlled via licensing and the Stationers Company in Britain. Finally, authors were the responsible parties — and Foucault says that is the birth of the author. 

We debate responsibility over the technology of AI today: Some want the model makers to be responsible for everything that could (or now could not) be produced from their machine. Some try to blame an application of the model (looking at you, Air Canada). Some want to blame the technology for making just what it was asked to make (looking at a certain lawyer and a certain reporter). 

The episode also reveals the fraud in associating generative AI with truth. If it were seen instead as a concordance of all society’s biased text and images and a creative tool that can be told to remake that, then there’d be no story here, only interesting reflections of ourselves, our aspirations, our faults, and our fears. 

The post Reflections in the ‘woke’ mirror appeared first on BuzzMachine.

Just a quick post to highlight my third and most recent appearance on 20VC with the amazing Harry Stebbings (Spotify, YouTube).

It is always, always a pleasure to speak with Harry. He’s such an effective interviewer that you quickly get into detail and stories that others miss. So you end up with very rich content, which in this case lasts significantly longer than 20 minutes. (More like 72, but who’s counting?)

In this episode we hit on a wide range of topics including:

• The metrics that matter in SaaS today
• Why CAC Payback is flawed and CAC ratio is better
• Why you need to hire sales reps three-at-a-time (aka, modulo 3)
• How to forecast in 2024 and in general (keyword: triangulate)
• The biggest mistakes made in forecasting, and how sales management practices can confound the forecasting process
• Why renewals are harder than ever to get (but alas easier to forecast)
• What all this means for Customer Success (both the disicpline and the department)

I’ve embedded the video of the episode below. I hope you can make time to watch or listen to it. And thanks again to Harry for having me.

The post My Most Recent Appearance on 20VC with Harry Stebbings appeared first on Kellblog.

2023 is over, so it’s time to go through everything! In a special year-end episode, we review the biggest stories of 2023, what we’re thinking of the AI hype, how science fiction makes us think about the future, the worst villains in the tech industry, and what we’re watching in 2024.
 
Gita Jackson is a journalist and cofounder of Aftermath. Molly White is the creator of Web3 is Going Just Great. Aaron Thorpe is co-host of Everybody Loves Communism.
 
Tech Won’t Save Us offers a critical perspective on tech, its worldview, and wider society with the goal of inspiring people to demand better tech and a better world. Support the show on Patreon.
 
The podcast is produced by Eric Wickham. Transcripts are by Brigitte Pawliw-Fry.
 
Also mentioned in this episode:

• If you become a Patreon supporter before the end of the year, you’ll be entered into a giveaway for five signed copies of Joanne McNeil’s Wrong Way and Paris Marx’s Road to Nowhere. Sign up now!
• Gita recently launched Aftermath, and you can go subscribe!
• Molly is getting started on TikTok. Go follow her!
• Aaron posts a lot of cool science fiction art over on Twitter. Give him a follow!
• You can see the Elon Musk and Jeff Bezos photos we discuss in the Worst Person in Tech segment on Twitter, Bluesky, and Mastodon.
• Paris was mistaken: Enya sang “May It Be” for Fellowship of the Ring, not “Gollum’s Song” for the Two Towers. That was Emilíana Torrini. But Paris listened to both of them too much.

Support the show



Download audio: https://chrt.fm/track/18859/www.buzzsprout.com/1004689/14211633-the-year-in-tech-2023-w-gita-jackson-molly-white-aaron-thorpe.mp3