A lot is happening, including AI making its Olympic debut and many other significant events! Before we dive in, here’s the TLDR of what’s in this month’s article and a sneak peek of other Fusionist activity behind the scenes.

The Short Fuse (TLDR)

AI Makes Its Olympic Debut and More…

It has been very busy and tumultuous the past few weeks. I’ve packaged up an easy-to-read summary of the top 5 events over the past month and their potential impact on humanity for your reference and easy reading, with validated sources available to dive even deeper should you desire.

In short, we’ve seen

1. A presidential assassination attempt and the sitting president stepping out of the current race

2. A massive technology outage affecting hundreds of businesses and millions of people

3. And team U.S.A. taking to Paris for the 33rd Olympics where AI is transforming operations, broadcasting, athlete safeguarding, and more.

I’ve been focused on how AI might impact humanity overall and how we can predict some of the ripples across our deeply connected world. While AI is just beginning to influence these huge events, I have no doubt that it will soon attempt to predict their outcomes with varying degrees of accuracy.

The 1-2-3 Approach to Leveraging Generative AI

• Download my 10-slide presentation to keep and share with others.

• Watch my 30 min. learning lesson with examples and Q&A.

Using Generative AI is as easy as 1-2-3! Seriously, it’s a powerful tool that, with the right systemic understanding, you unlock a whole new way of operating, learning, and producing.

1. Start with Prompt Structure — You can think of this like a Mab-lib. The prompt has become a crafting of your intent to better align with the thinking of a machine. However, with LLMs, that thinking is now more or less the logic we would use with a human colleague.

   To get the most out of working with an LLM, you have to think a little bit like a machine. Machine logic likes loops, explicit references, and binary actions, as John Maeda references in his book How to Speak Machine. However, the way we can access those computational powers is now very similar to our spoken language.

2. Guide the Conversation — The bulk of the work is having a general sense of the process or flow steps to get from where you are to the outcome you’re looking for. With computational power now closer to spoken language, we can converse with things rather than iterate through test problems. But the steps are basically the same.

   Just like working through an idea with a colleague, you can guide the output, intent, and discourse toward a better understanding of the problem, better formatting the output, and building on the knowledge collected over the conversation. You can see a simple version of this in my previous example using Perplexity to gather the Top 5 Events and Their Potential Impact on Humanity.

3. Apply Your Expertise to Finalize the Results — Lastly, having some guidelines for post-editing your results helps transition your generative AI content into something real. You control the results you share, which means you still hold the critical power of determining how to correct, elaborate, re-format, etc., any answer generative AI gives you. Leading with AI is not intended to be perfect for whatever it generates. It will produce something, but often it will lack something, have gaps in its logic, or even present something inaccurate that requires correction.

   The generated content will still need your expertise to correct, validate, and frame the outputs correctly. The post-edit of every generative AI output is what experts will now spend more of their time doing.

That’s it. I could elaborate further with some examples or share a use case with you (or 10), but it’s really that simple. If you want to see it in action, I posted the presentation for you to view or download. You’ll get an example prompt format from Product Forge that I use all the time in the presentation and more. I walk through each of these steps with examples in my talk as well. Check it out, and let me know in the comments what your favorite use of generative AI is so far!

The Top 5 Areas AI is Poised to Disrupt

The impact of AI on humanity over the next three to five years will be profound, reshaping various aspects of life from personal productivity to global economic structures. While AI offers significant benefits, such as improved healthcare, personalized education, and enhanced productivity, it also presents challenges related to ethics, privacy, and job displacement.

Understanding these impacts through the SHAPE Map framework and considering the rippling effect across Self, Society, Civilization, Humanity, Earth, Universe, and Existence, we gain a more holistic view of AI’s disruption potential. I’ve gathered the top disruption potential areas we can see so far that will have the greatest magnitude of change within them.

By examining AI’s development and deployment across these spheres, we can better navigate its potential benefits and risks, ensuring that AI advancements align with ethical standards, societal values, and human well-being to guide its development toward helping humanity instead of harming it. Here are the top 5 areas to be disrupted by AI as of today.

Top 5 Disruption Potential Areas

1. Healthcare Transformation

   AI's diagnostic and surgical capabilities promise significant improvements in patient outcomes and operational efficiency, potentially transforming healthcare delivery. The magnitude of this disruption is high due to its direct impact on health and well-being. However, its impact will be limited due to the high cost of entry for cutting-edge technologies unless the manufacturing, healthcare, and insurance business models also speed up traditional cost-reduction trends. We are already seeing material progress in cancer detection studies focused on Stage-0 breast cancer, giving patients and doctors a significant lead toward elimination.

   Learn More: (Nature Communications and VKTR)

2. Educational Evolution

   Personalized AI-driven learning systems can tailor education to individual needs, enhancing learning outcomes and engagement. This disruption will require educators to adapt to new teaching methods and technologies, which we’re already seeing. While the evidence so far is limited, it strongly suggests that the role of the traditional educator will shift from sharing new knowledge to sharing how to think more critically about the knowledge students discover. We saw the initial scare for teachers when OpenAi’s ChatGPT was released, which allowed students to generate essays in seconds. As tools produce high-quality results, students should embrace their power to synthesize and pose back to students how they can identify what is incorrect and then what matters most from the results they receive.

   Learn More: (The74 and The Harvard Gazette)

3. Job Market Reshaping

   It has long been the argument that AI will replace jobs, but lately, it’s easier to specify that AI-driven automation will only displace certain job categories while creating new roles in AI development, maintenance, and AI-enabled services. The disruption in the job market will likely necessitate extensive reskilling and workforce development initiatives. I’ve heard it often touted by thought leaders that “AI won’t replace your job, but the person who can leverage AI will,” a sentiment I agree with at The Fusionist. The future is unclear because employers and employees will be equipped with AI tools to make each of them more attractive to others, but building trust will be more critical than ever as fake information, lies, and fluffy language will be much easier and democratized. Technical roles like product engineers are already seeing gains in code production, but I suspect more strategic roles will see a shift away from selling knowledge to selling a more predictable perspective.

   Learn More: (Thought Collective and Standford’s Digital Economy Lab)

4. Privacy and Ethical Challenges

   The pervasive use of AI raises significant privacy and ethical concerns, necessitating robust regulatory frameworks and ethical guidelines to protect individual rights and ensure transparency. Web-based technology companies have been protected by laws like Section 230 of the Digital Millennium Copyright Act (DMCA) of 1998, which defines them as intermediaries and unculpable for content shared on their platforms. AI-powered bots, marketing generators, and propaganda are further pushing the limits of what may be egregious and calling into question how to manage harsh realities like hate speech, fake news, and threats at scale. Like other disruptors, AI will likely contribute to both the problem and the solution, leaving the end result up to those who will use their new superpower for good vs. evil.

   Learn More: (Pew Research Center and Goldman Sachs)

5. Environmental Impact

   AI’s substantial energy consumption presents direct environmental challenges. It turns out that training popular LLMs like OpenAI’s GPT3 produces as much CO2 emissions as “five cars in their lifetimes.” Developing energy-efficient AI technologies and promoting sustainable practices are crucial to mitigating the environmental footprint of AI advancements. Sustainable solutions for mitigating the environmental impact of larger, hotter, and more power-hungry data centers will likely be found using the same technology that is causing the issue. This paradox will likely reshape how we think about the future of computing and its impact on our planet.

   Learn More: (MIT Technology Review and Earth.org)

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One Last Thing…

I’m nervously excited to share with you that I’ve been working on a podcast for a couple of months now, and you all are the first to hear about it! My co-host, Tom Warson, and I get together for about an hour each week to have fun sharing our passion for product delivery, career development, and various paradigms that shape how to make our next big move. It’s a conversation between us that we think others will find valuable and entertaining, from stories about how people get from “here” to “there” and tips for better navigating the uncertainty along that journey.

I hope you like it. Our first few episodes are brilliantly dubbed “Jon & Tom Sart a Podcast (haha 😉), because this too, is figuring out our next big move. Enjoy this exclusive pre-release pilot episode, and let me know what you think.

Additional resources to help you Think Beyond the Feed!

• How to Think Like A Fusionist

• The Fusionist Guide to Leveling Up

• Technology at a Human Scale

Thank you for joining my journey of sense-making and navigating our techno-sapien condition. Stay vigilant, my friend. Cheers!