In the 80s and 90s, technology exploded. I was fortunate to be a young man who not only witnessed the transformation but was in the thick of it, helping design and implement systems that have changed the way we work. I have lived long enough to see the beginning of the second wave of technology that holds great promise of change: AI.
What we have forgotten (and some of you can be forgiven, as you were either small children or not even alive during those decades) is all the promises made about the coming age of silicon. Many of these have been conveniently forgotten as they did not come true.
These are some of the many promises that fueled our hopes but ultimately remained unfulfilled, highlighting the gap between expectations and reality.
- We would fully map the human genome, and all diseases would be cured (we have mapped the human genome, but it has not led to the eradication of diseases as hoped).
- Productivity efficiencies would lead to goods and services being continually cheaper. For a short, glorious moment in the late 80s and 90s, this actually. happened. And, well, we know what happened after that.
- Poverty and income inequality would be eradicated.
- The free sharing and access to information would lead to the fall of dictators and totalitarian governments.
Not only did these promises fail to bear fruit, but we are only now beginning to examine the negative consequences of technology on our societies, particularly on young people (as Jonathan Haidt’s excellent and well-documented “The Anxious Generation” documents). We saw unlimited potential in technology, but instead it delivered Facebook and X. We envisioned a free flow of information, and what we received is governments actively censoring SM and the MSM implementing ‘fact checks’ using literal Orwellian language.
AI will suffer the same fate. It is easy to blame the technology. But understanding that humans are central to its success or failure can empower you to shape outcomes. Recognizing that humans are broken, messy, and will find ways to use technology to hurt others emphasizes the need for deliberate effort and responsibility in AI implementation.
It’s also humans who are unable to help themselves in setting unrealistic expectations for technology’s potential. They conveniently ignore principles such as the conservation of information and the law of physics to make claims about LLMs that can’t be true even if we had true artificial intelligence (we don’t).
LLMs will evolve and impact industries, but there is no simple solution. To benefit from AI, you must thoughtfully embed it into your current technology and workforce, not seek an easy fix.
My company, Trinsic (www.trinsictech.com), developed the AI application CallSniper (callsniper.ai) to demonstrate how AI, integrated with traditional code and algorithms, can make a significant impact. CallSniper reveals bad calls for QA agents working in TAS and
call centers with a 95%-98% accuracy. CallSniper was undoable before AI, but is not possible with AI by itself.
Many AI and tech companies are not taking this route. Their current path suggests they believe there is an ‘easy button’ for AI. This misconception can lead to disillusionment. Setting realistic expectations helps build trust and prepares you for the effort required to realize AI’s true potential.
AI can enable strong productivity gains for your employees. There is no easy button for it. It requires forethought, planning, and careful integration into your technology stack. For those who do so, they will have a competitive advantage in the future. Get rid of the easy button, roll up your sleeves, and do the hard work. There will be rewards for those who are willing to do so.
