The second annual Ai4 Finance was a peek behind the curtain of what goes on in the world of tech-driven financial theory and practice. Being a hardcore fan of the show Billions, by far the favorite attire I saw during the conference was a t-shit a young man about my age was wearing that read: STRAIGHT OUTTA COMP.

Tickets for the two-day affair cost the security deposit and first month’s rent of my old Brooklyn apartment. (I have since moved back in with my family in New Jersey, because the NYC price-points are more-or-less anti-writers and anti-artists. These are not the days of Jack Smith, and Laurie Anderson, and Lou Reed, and Richard Hell. This is still Bloomberg’s “millionaire playground.” And I had to self-evict, simply to pursue art and writing.)

In all honestly, I was somewhat surprised that I was invited to cover the event given my literary corpus, general tech-skepticism, and peer group of mutual outsider-yet-popular writers and techno-thinkers, that would have also utterly hated what went down at this two-day long con.

It’s not that I don’t like technology, it’s that I am not what you would call an “early adopter.” I think most of it is very innovate garbage. When it comes to some new tech, or gadget, or system, or software, I am almost always the last person in the room to be convinced that it is actually “useful,” or even “a good idea.” I am no luddite, but I am no pushover either.

Nevertheless, I learned a lot during the conference. While doing so, I realized that I probably knew less than anyone else in attendance. This was made Poland Spring clear when a perfect storm of jargon, vernacular, and acronyms from the deep realms of AI, information science, and finance collided upon my neophyte being— leaving me very much the ignorant civilian-buoy left in a debris field to pick up the pieces and try and make sense of things.

Much of it I admittedly did not fully understand. It was not a language I was entirely familiar with. I know more about the history of physics and philosophy than I did this heady, economic material.

But I did learn plenty.

The major points turned out to be something all people everywhere need to realize: Everyone is gossiping about how developments like AI and ML (machine learning) will change the face of daily human life. I don’t mean the idea of a Terminator running you down, or getting uploaded into the Matrix. I learned that AI and ML is going to effect the whole global market.

In fact, it is already happening. And these systems I learned about do not seem like get-rich-quick schemes. Not by a long-shot. It all goes much, much deeper…

The folks of Ai4 Finance taught me: (1) These fintech ideas are major investment opportunities — this is not merely a belief among the economic industry; it is a reality. (2) Hundreds of major companies are actively attempting to adopt or already have adopted AI and ML technologies. (3) These systems will reach into every major market on the planet. This is not simply a goal, it is already underway. And I really cannot emphasize that realization enough.

My feeling was that not only was I deeply ignorant about the scope of this techno-economic development (my attention has been on Artificial General Intelligence —the sci-fi AIs that are human-like thinkers, like Data from Star Trek), but that the great majority of Americans and citizens the world over are entirely in the dark about the scale, veracity, and dedication that all kinds of of companies, in all kinds of sectors, affecting all kinds of markets are singularly fixed on this one hope that AI, ML, Automation, and Robos (think robot-callers here) will vastly improve their ability to push capital gains.

Every company may be different, but they are all seemingly united on this particular front.

AI means money, if used effectively. The more automated you are the more money you could make, and so on.

The first speaker was unambiguous: “Our vision here is to make every company an AI company […] Your data needs it’s own AI.” This was how the day started. It was impossible not to see what was being pitched as a kind of technologically-driven financial arms race. And it made sense. If your company is using these technologies then the perception is that these techs will give you an advantage over those who don’t. Right now if your company has some kind of AI or ML related program you are 15–50% times more likely to get funding than other tech projects.

One speaker set the stage dramatically, but to me, now, accurately, “We are on the outbreak of war.” I go to conferences. I like them.

I have been to conferences on AI. I was even on a panel discussion about ethics and AI at South Korea’s Block Seoul event back in September 2018. But this statement caught my attention, partially because it was also maybe 10:30 am in the morning. Definitely well before lunch. And I hear this.

According to one speaker out of a survey of about 800 enterprises, 80% had already adopted an AI or ML platform, and that these companies expected such systems to increase total gains by 33%. That’s major. Whether or not it actually pans out that way, it started to dawn on me that this is what conferences must have been like just as banks started to understand the real meaning of the internet, the personal computer, and the inevitable dotcom boom back in the 1980s and 90s.

“Let’s say you’re dealing with a small portfolio. Say 100 million dollars […]” That was my ‘Where the fuck am I right now?’ moment hit. This, again, was early in the day. Were they ball-busting each other with lines like that? Or, is 100 million dollars like a poor ass portfolio these days?

Citibank was there. NASDAQ was there. I was where people responsible for hundreds of billions of dollars worth of assets meet up and shoot shit. It was my financial conference cherry popping—and they all were selling, pitching, researching, pushing, and installing AI. And I was all, “Whoa, motherfucker,” about it.

Another big league speaker made it brilliantly clear to a novice like me—he explained that one of his roles is helping individuals and companies understand what AI and ML really means for the world; “AI is going to be like electricity. It’s going to be everywhere.” Companies without it are going to be left in the dark.

This is a pitch talk from three years ago on FinTech. The talks at Ai4 Finance were far more detailed and specific.

Many have thought about how AI, ML, Automation, and Robos can (and probably will) replace labor forces like truck drivers, warehouse workers, and retail cashiers. But people-less banks were brought up; Robos running banks. And it goes further. Robos replacing financial advisors. Robos calling you up and telling you not to sell while everyone else is selling, easing your fiduciary stress during moments of tension.

A recent article in the Wall Street Journal brought up how automation, drones, and Robos can be used in the real estate sector:

The next time you buy a house, your lender might deploy a drone and a computer algorithm to size up the property instead of a tape-measure-toting human appraiser. Federal regulators are moving to allow a majority of U.S. homes to be bought and sold without the involvement of licensed appraisers, by increasing from $250,000 to $400,000 the value of homes exempt from a human evaluation.

Elon Musk recently said that AI will make most jobs “pointless.” The World Economic Forum expects 75 million jobs to be displaced by 2022 (three goddamn years.) And, even more alarming to an outsider like myself, the last speaker of the first day said: “AI will both create and destroy hundreds of billions of dollars in the next ten years.”

The folks at the conference seemed rather pumped about all these developments. I probably would be too if I were them. They were already on the ground-floor of this (now I believe to be) inevitable reality. One speaker said, “Traditional business sense” is necessary for any AI to succeed. Although business savvy is likely helpful, that alone is really not even remotely enough.

We are honestly dealing with something like an alien. And the leaders of finance are putting their total faith in it.

Another speaker, one who had authored several respected papers, was particularly explicit: It might be impossible to ever actually understand what is going on under-the-hood of AI and ML. Computers already out-calculate us, and it may be that AI and ML might out understand us as well. It’s true. My understanding is that sometimes AI and ML systems come to conclusions that even the data scientists and engineers monitoring the technology cannot entirely explain or account for. That means even the people who design and implement these kinds of techs have absolutely no idea how these systems come to answers that they arrive at. This is called the “black box” problem in the industry.

Jack Dorsey, CEO of Twitter, has gone on the record admitting, “In fact, there’s a whole field of research in AI called ‘explainability’ that is trying to understand how to make algorithms explain how they make decisions.”

Over and over again I heard the phrase “wild west” at the conference — which, to me, is really just another way of saying “the freedom to not know what we are doing., but doing it anyway.”

Imagine the chaos and more-or-less casino of global markets as they already are today. The question is: will these AI-directed systems bring order to the noise? Or will they open even more expansive vistas of confusion? Either way, if you trust what an AI or an ML brings to process market analytics, customer profiles, or whatever, it means that these systems are, in a sense, running the show.

Are these AIs just the next personal computer? I am not so sure. I tihnk they are basically computational aliens now, that many have put blind faith into.

We can explain how a computer does what it does. But, how AI and ML work, not so much. No matter how AI turns out, I realized that these folks were talking about a revolution of sorts—one already underway.

Ai4 Finance was conference that was my personal wake up call. The problem is Americans have largely no idea at all about the impact that these systems are already making on our economy and our labor force. Before this conference, I was one of them. I am not anymore.

When I think about the fact there would be no way I could afford to attend such a conference, I realized that there are no real safety nets for the businesses and workers who do not use AI, or ML, or Automation, or Robos at this time. Remember, 75 million jobs gone in just a little over one thousand and one hundred days—three years—according to these money-grubbing masters of the universe. That’s the World Economic Forum’s own timetable.

This made me deeply appreciate Democratic nominee Andrew Yang, who has been sounding the alarm over automation, AI, and the like; and who is currently running for president.

I kind of wish he would join forces with Bernie Sanders and they could both discuss poverty, job displacement, and the new techno-computer-automated force that is probably far-less than ten years away from displacing millions upon millions of jobs the world over. If only Congress itself could catch up.

One of the most professionally seasoned speakers touched the poet in me when he said, “Software is eating the world.” That was beautiful to me. And it feels true. We happy consumers have to really get a clue. We are so wrapped up in proprietary software. We breathe out gigabytes of data to unseen corporate hiveminds without a care in the world. It is high time that humanity puts systems in a place that ensures that software does not eat us all along with it.

Some speakers did bring up ethics and how if mining out metadata from users is part of your covert business model (like fucking Facebook) then you’re probably an asshole that should really reconsider that mode. But companies are legally required to maximize profit.

How will those ethics workout when AI’s involved? Again, Yang, Musk, Harris, Rushkoff, Bostrom, Case, and even Joe Rogan are among the few that are really trying to get the public to understand the absolutely tidal shift that is covertly surrounding and invading our moment-to-moment existence.

Kai Sedgwick wrote a piece on cryptocurrency and artificial intelligence that closes with an important sentiment: “[I]ts invisible hand is already pulling strings within the sector, facilitating everything from faster order execution to detecting bots and scammers. Our AI overlords are already here.”

“Who rules the world when the algorithm rule themselves?”

The best thing you can probably do for yourself today is to watch at least one YouTube video on it.

Even better, find out who is this Andrew Yang running for President.

Finally, understand that just because you cannot see it in your face does not mean it isn’t already there and effecting you.

Everyone now knows the uncanny moment of thinking or talking about a product or need and then poof, an ad for it shows up on one of our feeds. Recognize, that is the work of AI and ML.

I cannot help but recollect the great actor Raúl Esparza as Fredrick Chilton in the television show Hannibal when he says, “You cannot see it, and you will not see it until it is too late. Don’t say I did not warn you.”

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