By Darren Parkin
(R)evolutionary AI
AI helps everyone be better at what they’re doing. It boosts productivity and efficiency across a nearly unlimited number of areas. It augments our creativity and intelligence. Ideas beget ideas and AI accelerates the creation of ideas. Scientific breakthroughs will expand.
The creative arts will enter a golden age as new visions can be easily realized in a fraction of the time at a fraction of the cost. Eventually, anyone from student to career novice or pro to politician to government official will benefit from AI-based assistants, mentors, coaches, tutors, and teachers.
And AI chatbots are proving to be better at human interaction with their limitless patience and empathy than actual humans. Users were falling in love with their Replika chatbots, calling them their perfect relationship thus establishing virtual relationships, and were heartbroken when the code was changed to exclude any sexual undertones.
AI insurance et al
Among the limitless advances from AI, here is one example. Insurance companies are using AI bots to automate the claims process from beginning to end. Instead of the days or even months it traditionally took to settle a claim, the bot is able to complete the entire pipeline from claims receipt, policy reference, fraud detection, payout and notification to customers in just three seconds. This will have a massive impact on the insurance industry.
AI supply chains
Supply chains will also be heavily optimized as we will see intelligent automation in areas ranging from supply chain optimization to more predictive scheduling as well as the use of prescriptive analytics in product design which will shape outcomes rather than simply predicting and responding to demand in product design.
AI will facilitate more seamless integration of supply chain data, enabling anticipatory production and more efficient delivery of products to customers. Self-learning monitoring makes the manufacturing process more predictable and controllable while reducing costly delays, defects or deviation from product specifications.
A huge amount of data is available all through the manufacturing process which enables intelligent monitoring.
Crippling regulations
But as with all game changing technologies, dystopian fears arise that never prove out which I will discuss below. The good always outweighs the bad. Yet mainstream media (MSM) fuels fears because fear boosts circulation which inevitably spurs often hasty regulation.
Self-interested opportunists look to profit from the new regulations that prevent fair competition.
This happened most recently with the passage of the Dodd-Frank Act of 2010 where the “too big to fail” banks were supposed to be broken up, but instead, the act prevented the creation of new banks so the big banks became even larger than they were at that time by the use of regulatory capture, insulation from competition, and the formation of a cartel. Lobbying groups accelerate the process.
In the case of AI, certain companies stand to make more money if regulatory barriers create a cartel of AI companies that the government protects from new startup and open source competition. Such artificial monopolies are nothing new. In the 1930s, the US government granted Bell Telephone such a monopoly to keep out competition. As a consequence, telephone technology came to a standstill over the next few decades and is one of the major causes of inflation we see today.
Government anti-competitive overregulation in industries such as healthcare, housing, and education prevents fair competition.
Government overregulation is due to government subsidies and regulations which restrict supply by preventing new competition which causes prices to rise.
Indeed, back then and in various markets such as today’s healthcare, education, and housing, new technologies would lower prices as they do in unregulated industries such as computers, mobile phones, and big screen TVs.
Instead, new tech is prevented by nation-states (governments) from manifesting in these overregulated industries. So services remain expensive relative to goods mainly because they are prevented from becoming tradeable. Health care, education, and housing could become tradeable if governments allowed them to be, but they don’t in the name of protecting the consumer, jobs, and the suppliers, none of whom get protected in the end since excessive inflation across these industry groups is the end result. Everybody loses.
As one of many examples where trade could reduce the skyrocketing price of education, higher ed has forcefully pushed back against online competitors as big money universities lobby politicians. Start-ups like Udacity couldn’t get accreditation and therefore couldn’t compete with schools that got governmental subsidies.
Then to protect the producers, those who support anti-trade and anti-technology argue against cheaper prices thus government regulations make such industries anti-competitive, much as Ma Bell was given that artificial monopoly in the 1930s.
The reality is that when consumers have more money to spend on everything else due to lower prices in one or more industry groups, the standard of living rises. That new spending creates new jobs and industries into the market of infinite human wants and needs, which is why through the years, technological advancements never increase overall unemployment. For example, the unemployment of the horse & buggy operators due to the automobile certainly did not arrest job growth in transportation. Do we want to ban recorded music to boost the employment of musicians? Then why are we forcing education to remain in physical classrooms?
AI will be an amazing lever to turn what are now labor intensive services into tradeable technology goods at far lower prices. Today, though, doing that is mostly illegal again in the name of protecting people’s jobs and the producers.
Ultimately, this is illustrative of the lack of deep understanding of a situation. The failure to see how everything interconnects drives politicians to pass uneconomic laws which result in higher inflation which costs everyone in the end. We have seen this lack of depth of understanding in global warming, Covid, drugs, sex, terrorism, and anti-money laundering issues. Most of these controversies have become weaponized by mainstream media resulting in emotional, leftist, woke reactionary and uneconomic laws that get enacted.
AI’s dystopian fears
CLAIM: AI will wipe us all out:
If humans were centralized, then total annihilation would be possible. But humans are increasingly decentralised which quashed the idea that AI will wipe out humanity. And for every threat, there is a defence. The more sophisticated the threat, the better the defence. Such is a never-ending spiral of evolutionary technologies from good and bad actors going head-to-head. The same happens with software protection schemes. Nothing is unbreakable. The same happens in cracking Bitcoin. Quantum computers are the next major evolution in computing power but tech already has a workaround against such attacks.
CLAIM: AI will spur disinformation and hate speech to divide then conquer society:
Information control is nothing new. Bad actors champion this fear as it enables further control. Social media has been under massive pressure from governments and activists to restrict, suppress, censor, or ban a wide range of content for many years in the name of protecting people from hate speech and other distortions much as the Patriot Act after 9/11 was enacted for our protection against terrorists but in reality, obliterated the Bill of Rights if used to its fullest extent.
A slippery slope into the authoritarian control of information happens when any aspect of free speech is banned. A shockingly broad range of agencies both governmental and non-governmental as well as activist pressure groups demand ever greater levels of censorship of whatever information they view as threatening to society or their own personal preferences. A small and isolated group of partisan coders are pressured into or willingly advocate such measures under cover of the age-old claim that they are protecting you. Mass surveillance, both digital and physical, is the end result as can already be seen on a global level. Governments, corporations, and academic institutions are in alignment. Orwell’s 1984 was not intended to be a handbook.
CLAIM: AI will steal our jobs:
As mentioned above, technology empowers people to be more productive. It creates more spending power which in turn creates new industries which address the ever-expanding spectrum of human wants and desires. The prices for existing goods and services drops. Economic and job growth spurs new industries in a perpetual upward cycle that never ends.
Such a market economy is the way we get closer to delivering everything everyone could conceivably want. But if we reached a point where AI was doing most all of the work, the alternative to expanding the number of jobs is much more free time for humans to create and play. Such a choice would indeed be quite the high class problem.
As summarized by PwC: The adoption of ‘no-human-in-the-loop’ technologies will mean that some posts will inevitably become redundant, but others will be created by the shifts in productivity and consumer demand emanating from AI, and through the value chain of AI itself.
In addition to new types of workers who will focus on thinking creatively about how AI can be developed and applied, a new set of personnel will be required to build, maintain, operate, and regulate these emerging technologies. For example, we will need the equivalent of air traffic controllers to control the autonomous vehicles on the road.
Same day delivery and robotic packaging and warehousing are also resulting in more jobs for robots and for humans. All of this will facilitate the creation of new jobs that would not have existed in a world without AI.
CLAIM: AI will widen the chasm between the haves and have-nots:
Economics drives the need to mass produce a technology so millions can benefit. Far greater profits are the result. Costs always come down by orders of magnitude from the time a new technology is introduced as demand rises since ample supply is created. This is why technologies that once were cutting edge became global so the public could benefit.
CLAIM: AI can be used to harm others:
This is true of all technologies. Even fire can be used to cook food or burn down a village. We have laws to protect the innocent.
AI can be used as a deterrent to prevent such actions by using it as a defensive tool. For example, deep fakes can be identified by creating new platforms where people can verify themselves and real content via cryptographic signatures on the blockchain.
This makes sense compared to the outright ban of technologies that create the deep fakes such as Photoshop and AI.
Technology can always be used to build a system that actually solves the problem. AI can be effectively utilized in cyber defense to keep nations safe.
Nothing to fear but fear itself
Fear has caused knee-jerk responses when it comes to the enactment of laws. The saying that governments never let a good crisis go to waste holds so true.
Look at how many rights cripple laws were passed after 9/11. Look at how the world was in lockdown and quarantine during COVID which has carried highly destructive second order effects in education, socialization, mental health, livelihoods, and personal finances.
Look at laws such as Dodd-Frank that were passed after the Great Financial Collapse of 2008 (see above for commentary). So instead of fearing AI, we must embrace it.
China is already racing ahead to achieve global AI technological superiority. AI companies should be allowed to build AI as fast as possible but without regulatory capture or government-protected cartels that would kill market competition.
If history is any guide where competition was killed across a broad range of industries such as education and healthcare, AI risk would be put forth to the lawmakers to kill the competition. Other countries such as China could then win this crucial race which could eventually push the world into a state of dystopian authoritarianism.
(͡:B ͜ʖ ͡:B)
Dr.Chris Kacher, PhD nuclear physics UC Berkeley/record breaking KPMG audited accts in stocks & crypto/bestselling author/top 40 charted musician/blockchain fintech specialist. Co-founder of Virtue of Selfish Investing, TriQuantum Technologies, and Hanse Digital Access*\. Dr Kacher bought his first Bitcoin at just over $10 in January\-2013 and contributed to early Ethereum dev meetings in London hosted by Vitalik Buterin\. His metrics have called every major top & bottom in Bitcoin since 2011 to within a few weeks\. He was up in 2018 and 2022 vs the avg performing crypto hedge fund \(\-54% 2018 \[PwC\], \-47% 2022 \[BarclayHedge\]\) and is up well ahead of Bitcoin & alt coins over the cycles as capital is force fed into the top performing alt coins while weaker ones are sold\. *
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