With the public launch of Chat GPT in November 2022, we’re all in the midst of exploration and evaluation of the impacts from the explosion of Artificial Intelligence (AI) for public consumption.
Since that Chat GPT launch, a lot of the big players have released their public offerings, These include Microsoft’s Co-Pilot, Google’s Gemini, and X’s Grok.
At The Innovation Garage, we’ve spent the last two-and-a-half years diving deep on AI tools, both on our own and with our client base teams. Early on we received client requests for educating on AI basics. In these heavily requested AI primer sessions, with all levels of leadership, including client board level leadership. We have been reviewing and monitoring how our client teams are looking to adopt AI in their daily work.
In short, we’re all trying to determine if Artificial Intelligence is the real deal, or just an overblown hype show.
We are subjected to continuing bombardments of AI advertising, AI content and AI generated videos. All heavily marketing AI as the next big thing. AI is now force fed in our tech stacks and email tools without an “opt-in” option. This continuous bombardment of AI in our tech stack tools and social media feeds is driving continuous context switching in our brains.
If we understand the what and the why this is happening, it can set us off in multiple and sometimes very distracted directions. The outputs of which is causing misalignment across organizations and their long term strategies. Each of our clients, is trying to suss out using their very own 5D organizational brain chess, an ideal path forward. Clients are ruminating on the following key questions;
What actually is this thing called AI? How will it help our team in what we do? And, in the worst case scenario for some, grappling with the critical question; will AI will replace the role of some humans in our workplace, our systems and perhaps our own daily work?
The approach in this article series is to provide a basic primer on AI. Coupling that primer with our best critical thinking to date. We’ll present insights of what we’ve learned so far. We will share what clients are experiencing in their own AI discovery.
We’ll also want to time travel back a ways, exploring the historical cycles of new technology. Looking at those historical cycles of technology presenting to the world as the next savior, and what actually has manifested over time with technology.
Finally, we will make some next step suggestions, on how to make your own individual determination of the ultimate value AI will (or will not) provide for both yourself and your organization.
Artificial Intelligence Primer – A brief history and the basics of AI.
The initial concepts of AI evolved in the 1950’s, with the work of Alan Turning asking the question, “can machines think?” John McCarthy is generally recognized as the person who invented AI with a series of lectures in the mid 1950’s.
Over the last fifty-five (55) years the concepts evolved into some of the basic building blocks that have become familiar today.
The overarching container is referred to as Artificial Intelligence. AI contains sub domains of Machine Learning and Deep Learning. As shown in the image below:
Deep Learning is at the core what is driving today’s AI explosion. Deep learning has introduced advanced solutions computer vision, pattern recognition and natural language processing.
Agentic AI or Agent Based AI, also called generative AI is based on prompting AI tools with roles or instructions to research of analyze data.
Artificial Intelligence & Historical Cycles – What may be the historical impacts of AI technology?
We touched on the importance of understanding historical cycles in an earlier article.
“In their book, The Fourth Turning, published in 1997, the authors Howe and Strauss, discuss historical cycles. In looking back almost 500 years, the authors explain why most history repeats itself every one hundred years in twenty to twenty-five year cycles that the authors call “turnings.”
In the same way, looking at historical cycles from a past period the human behavior observed from a past period can help inform a future prediction. To better understand the technology introductions we face today, all you have to do is go back just one turning, to the 2000-2005 period in the area of global supply chain and operations.
During that period, supply chain practitioners spent time in corporate board rooms, sometimes presenting multiple Total Cost of Ownership analyses as part of a sourcing strategy. If you participated in those sessions, the dynamics in those meetings frequently went like this:
If a local supplier could not meet the desired buy price, a procurement team conducted a sourcing activity to find the lowest-cost provider. Many of those low-cost providers were early-stage companies usually located in the Asia Pacific region. Almost every time, the Total Cost of Ownership analysis indicates a slight to moderate savings of offshoring compared to localization.
However, due price pressures and public demand of not being concerned with where the product was manufactured, the off shore decision was made. People wanted cheap goods, and didn’t really care where they come from. During this period an enmasse decision was made by many organizations to ship the technology and manufacturing overseas. The supply chain historical cycles analogy is now repeating itself. This time with AI.
Instead of outsourcing technology and manufacturing, AI tools are being positioned to outsource a humans ability to think critically, communicate effectively and to build their own independent and meaningful skills that provide value to others. If organizational leaders have a minimal concern from where the work comes from, AI integration will appear to be the best and lowest cost decision option for the organization.
The Smart phone came on the scene on a massive scale in 2010. Studies have pinpointed that with the advent of the smartphone we actually have already experienced cognitive decline.
In a similar vane, with that the arrival of social media, studies indicate the same thing has happened. Our personal connections with others have diminished and for many people, the feeling of isolation has actually increased.
We predict that historical cycles will show that outsourcing of critical thinking to AI will, over time, historically prove to be a poor choice. The hangover from decisions being made today will manifest in the population in five (5) to ten (10) years down the road. These trends indicate that the average person, will not apply critical thinking in their choices, and will be more than happy to outsource their thinking to AI. It’s popular and easy to do, avoids conflict, difficult communications and tough decisions for the individual person and the organization. It is now a very easy and extremely comfortable approach to take.
Artificial Intelligence in the Real World – What is the AI business model?
Is AI the next transformative technology or the next grift? To gain some insight let’s take a look at some recent insights on the topic.
- In a recent article by Jason Lemkin he indicates that data shows that AI startups burn through cash twice as fast as previous startups.
- PE firms have poured over 1 Trillion dollars in Artificial Intelligence over the last twenty four (24) months.
There is a standard business model that for Artificial Intelligence which is starting to manifest:
- Free access for a limited time, then “hook the user” with low cost initial subscriptions and subsequent future price increases or “free to use” with embedded advertisements.
- Private Equity (PE) firm’s offer up a pile of cash to build up an initial user base, then once a threshold and set point is reached, creating sticky dependencies with the user base. Changing the free model to subscriptions for recovery of the initial investment and recovery of the PE cash burn that built up the initial user base.
- Most executive leaders do not yet understand that AI enterprise subscriptions do not include unlimited access to AI tokens.
Artificial Intelligence and Cognitive Debt – Studies Indicate the Cognitive and Emotional Debt is Real.
Evidence is demonstrating heavy Artificial Intelligence use results in “Cognitive Debt.” Several recently published studies are indicating that AI use creates cognitive debt in those that become heavy users.
https://www.media.mit.edu/publications/your-brain-on-chatgpt
https://time.com/7295195/ai-chatgpt-google-learning-school
To gain your own understanding of what cognitive debt is, without the aid of technology, consider these three simple questions:
- From memory, can you recite the top three (3) to five (5) phone numbers of your closet family or friends?
- What direction is North, South, East and From your current location?
- Do you have access to and would you know how to read and navigate from a printed map?
If you can answer the above without use of technology, you would likely be in the minority. Most of these previous life skills of easy recall and self navigation have evaporated for the majority of the population indicating a cognitive debt exists.
In one recent and practical example, an AI education program attendee shared their own personal narrative and relationship with Chat GPT. Essentially, looking to use Chat GPT in the role of a personal life coach. They described the process of over a two year period, having built a personal relationship with the AI agent.
Over time the session attendee has placed the AI agent in a role of both a close friend and life coach. Providing daily guidance on the ideal responses to every day situations. The attendee described to us how the AI agent has over time, “really understood me as a person.”
Take from this what you will, but this a very similar (and discomforting) psychological trend within the various personas of the many leaders we know that are leaning into heavy use use of AI in their daily work.
Engaging Artificial Intelligence – Critical Thinking and Small Experiments are Key.
If you elect to engage an experiment with AI, as a basic foundation, as a first rule look to conduct simple and small scale experiments. As a second rule, don’t outsource your own critical thinking to AI.
Critical thinking at its essence, is the ability to have two competing thought paths in your mind at exactly the same time. At the simplest personal choice level, is this choice good, bad, or perhaps, could both be true? Critical thinking allows you to evaluate pros and cons of decision paths in parallel and make the best decision based on your own research and conclusions.
For your own thought experiment, apply your critical thinking skills and ask yourself the following series of though starter questions of AI as a technology:
- Do you understand what your Artificial Intelligence models being considered are actually trained on? Understand the basics of AI and what input data is used to train the AI model. Most all publicly available AI tools have their historical knowledge base established by scraping the internet and social media feeds. Understand that the simple saying of “garbage in = garbage out” applies with AI training models.
- “Is the potential “cost” of your Artificial Intelligence engagement decisions something you will be happy with in the long term?” Most AI early adopters and super users pay a price and gain speed in the short term. It is clear they likely they do not understand nor are factoring in the long term cost and potential risk.
- Are you engaging with Artificial Intelligence because everyone else is, or have you discovered where AI can truly help both your individual and organization’s skill sets? Be mindful of the peer pressure to be part of the “in” crowd and the damage that may result if you elect to engage heavily with AI.
- What Artificial Intelligence experiments has your organization conducted? Experiment and learn how to prompt. In this way, as you conduct your own prompting experiments, you can make your own determination on value of AI for yourself and your organization.
- Are you about to make a significant Artificial Intelligence investment? If you or your organization is considering investing in AI, look for the presence of the important standard and classic business case elements of ROI and look for proven use cases before investing. Avoid shiny object syndrome at all costs when considering an investment.
Embracing Artificial Intelligence – Trends and Countermeasures to Explore.
We offer the following observations and countermeasures for AI consideration and investigation both at the individual and organization level. If you’re going to use and engage with AI, make sure to use and validate AI technology as a meaningful amplifier of your analog and human centered methods. Look to ensure human interactions and craftsmanship remain in your long term strategy. As for the trends here is an initial analysis:
First, we do see a few Artificial Intelligence trends that are emerging, here’s a quick list of elements we encourage you to explore:
- Internet Search – AI tools do a good job of finding results faster than traditional search. This works especially well if searching for products to purchase. You will likely see the significant reduction of the traditional internet search we have become accustomed to. You are already witnessing the embed of AI tabs in internet search browsers and AI enhancements in typical tech stack tools.
- Research Validation – AI research and insight does provide alternate references and insights, if as mentioned above, you apply traditional analog research approaches first, then validate the AI results as a secondary step. Sequencing your workflows in this fashion provides alternate paths to explore outside of your initial inputs. Remember to validate the results.
- AI backlash – User reports of incorrect information, analysis errors, hallucinations, code errors, difficult and impossible to rework AI vibe coding, and high subscription fees are now being reported. These are real data points of the Snake Oil component of AI.
- AI will likely be a scapegoat – AI will be used by many leadership teams as an excuse to justify job reductions and mass layoffs as air cover for poorly run organizations.
- Human Interaction will win the day – With the AI backlash starting, this means that offering human interactions becomes the ideal countermeasure in response to the present day AI obsession. Your organization and your customer base wants and needs human interaction and they will thank you for it.
Second, experimenting with AI in small doses and continually reviewing the AI tool outputs is a good practice to become adept at. Contrast the AI outputs against a well designed and well understood human centered process. As mentioned earlier, don’t forget the business fundamentals and the return on investment for your future Artificial Intelligence investment decisions.
Third, and most importantly. Celebrate and maintain your human interactions and process design. Don’t give up on human craftsmanship. Keep your analog and human centered approaches in what you do and if we can be so bold, double down on them. Analog methods first and always.
Artificial Intelligence Prediction – Technical Savior or Carnival Snake Oil?
Our prognosis and the verdict thus far. Don’t believe the AI hype. Most AI is much more “Snake Oil” than technical savior. Most AI software solutions we have seen have been cleverly dressed up and rebranded as AI or “Agentic” agent based tools.
Many of these platforms, work in exactly the same way in which they always did. Now presented with a refined and polished AI marketing tagline. The refined tagline does little to the underlying code and functionality of these tools. It’s primarily a new coat of marketing paint.
Our prediction is that the continued expanse of Artificial Intelligence in the public domain, will do nothing else beyond creating more technical, cognitive and psychological debt for the general population. In summary, as a global culture, we will continue to see a long term increase in human mental, cognitive and emotional fallout.” – The Innovation Garage
As a technical savior, our experiments and insight indicate that much of AI is a “this too shall pass” solution. Using our own critical thinking from the presented analysis, and our understanding of historical cycles, we are seeing continued negative evidence that informs a bold prediction. The prediction is that, for the most part, Artificial Intelligence is an overblown hype show.
To read more on this point, we encourage you to pick up a copy of “AI Snake Oil” by Arvind Narayanan & Sayash Kapoor and consider subscribing to the authors substack page.
So, recall the carnivals and county fairs of your past and the snake oil carnival barker selling their “cure-all” remedy. If you’re jumping into an AI tool acquisition and potentially significant investment for the sake of being fashionable and on the leading edge with AI, be prepared to be disappointed and note the following:
- AI will not fix an organizations’ culture.
- AI will not fix a broken process.
- AI usage is will continue to be creatively monetized by the service providers.
- Heavy AI Users will become overly dependent on AI to do what once was a typical human cognitive task.
- The publicly available tools are, for the most part the next mainline version of the technical dopamine machine.
- Remember that you and your prompt inputs to AI are the product. Similar to internet search and the evolution of social media. Don’t be fooled into thinking it’s any differently with AI.
In summary, look to amplify what people in your organization do best. Which from our perspective, is to continue building with human creativity, connection, innovation and craftsmanship to make things that never existed before.
If you’d like to learn more about AI, check out The Innovation Garage AI primer session offerings. In these session we we explore high level strategies that will support your organization to sensibly explore AI for your organization. Take a first step by reaching out to us here, or drop an email to i[email protected].
At The Innovation Garage®, We help organizations grow. Providing education, tools, technology, and expert consulting in change management for strategy, innovation, and supply chain.
Guiding leaders from organizations across the world to intentionally self-disrupt their offerings and organizations. We deliver world-class education, tools, and technology on how to craft business operating systems focused on long-term profitable growth.