Capitalogix

The Illusion of Choice

What happens doesn't matter nearly as much as what you make it mean ... and what you choose to do. 

For example, Dallas has been 100+ degrees almost all summer, and nothing stops.  You'll see people running outside, dogs walking, sports being played.  My son plays 8+ hour rugby tournaments in that heat, and no one bats an eye. 

Growing up in New England, we were woefully underprepared for that heat.  The world would stop.  On the other hand, 8 inches of snow was nothing, but a little bit of ice ... and Texas shuts down. 

Snow isn't 'good' or 'bad' … and neither was the change of plans.

Perspective.

Fund managers recognize the importance of sensibly diversifying risks and opportunities.

Be that as it may, as Mother Jones reported in the wake of the 2009 financial crisis, the nation's ten largest financial institutions held 54% of our total financial assets (compared to the 20% they held in 1990).  Meanwhile, the number of banks has dropped from almost 15,000 to barely 4,000. 

via Statista

Many people are shocked by a chart like this.  It must be 'bad' to have so much controlled by so few, right? 

But it isn't hard to find a version of this story playing out in other industries:  Print Media,  Music,  Broadcast Channels, and Consumer Products … this type of consolidation happens for a reason.

A firm that marshals more resources gains a competitive advantage and has more ways to win.

They benefit from economies of scale, transactional leverage, better distribution and partners, and more ways to diversify risks.  In addition, if they work to communicate, collaborate, and coordinate their actions (and data), they can unlock opportunities that others don't have (or can't see).

Here is a Chart Showing Some of the 'Winners' at that Game.

The following chart highlights our "Illusion of Choice."  A surprisingly significant portion of what you buy comes from one of these ten mega-companies (Kraft, Coca-Cola, PepsiCo, Kellogg's, Nestlé, Proctor & Gamble, Mars, Johnson & Johnson, General Mills, and Unilever).

It's amazing to see what these giants own or influence.  Click the picture to see a bigger version.

via visualcapitalist

Here is a more specific example.  You probably think you are familiar with Nestlé.  It is famous for chocolate.  But did you realize it was an almost $300 billion corporation … and the biggest food company in the world?  Nestlé owns nearly 8,000 different brands worldwide and takes a stake in (or is partnered with) many others.  This network includes shampoo company L'Oreal, baby food giant Gerber, clothing brand Diesel, and pet food makers Purina and Friskies.

Kind of cool?  Mostly terrifying...

Gartner's 2023 Hype Cycle For Emerging Technologies

I share an article about Gartner’s Hype Cycle for Emerging Technologies each year.  It does a great job of documenting what technologies are reaching maturity and which technologies’ ascents are being enhanced by the cultural zeitgeist (hype, momentum, great timing, etc.).

Creating a report like this requires a unique mixture of technological analysis and insight, an acute understanding of human nature, and a lot of common sense.

Identifying which technologies are making real waves (and thus will impact the world more) is a monumental task.  Gartner’s report is a great benchmark to compare with your perception of reality.

A quick look back at past reports shows that 2021 saw the inclusion of NFTs and advancements in AI.  It also focused on the increasing ubiquity of technology.  2022 built on those trends, recognizing that we were moving towards immersive experiences, faster digital transformations, and the adoption of exponential AI capabilities.  For reference, click here to see what Gartner predicted last year.

Meanwhile, let’s look at the 2023 version of Gartner’s Hype Cycle for Emerging Technologies report.  2023 has some meaningful changes – and is best understood by where things are placed on Gartner’s framework called the “Hype Cycle.”

What’s a “Hype Cycle”?

As technology advances, it is human nature to get excited about the possibilities ... and to get disappointed when those expectations aren’t met. 

At its core, the Hype Cycle tells us where in the product’s timeline we are – and how long it likely will take the technology to hit maturity.  It attempts to tell us which technologies will survive the hype and have the potential to become a part of our daily lives. 

Gartner’s Hype Cycle Report is a considered analysis of market excitement, maturity, and the benefit of various technologies.  It aggregates data and distills more than 2,000 technologies into a concise and contextually understandable snapshot of where various emerging technologies sit in their hype cycle.

Here are the five regions of Gartner’s Hype Cycle framework:

1. Innovation Trigger (potential technology breakthrough kicks off),
2. Peak of Inflated Expectations (Success stories through early publicity),
3. Trough of Disillusionment (waning interest),
4. Slope of Enlightenment (2nd & 3rd generation products appear), and
5. Plateau of Productivity (Mainstream adoption starts). 

Understanding this hype cycle framework enables you to ask important questions like “How will these technologies impact my business?” and “Which technologies can I trust to stay relevant in 5 years?”

That said - it’s worth acknowledging that the hype cycle can’t predict which technologies will survive the trough of disillusionment and which ones will fade into obscurity. 

What’s exciting this year?

Before focusing on this year, it’s important to remember that, in 2019, Gartner shifted towards spotlighting new technologies at the expense of technologies that would normally persist through multiple iterations of the cycle.  This change helps account for the increasing number of innovations and technology introductions we are exposed to compared to the norm when they first started producing this report.  As a result, many of the technologies highlighted over the past couple of years (like Augmented Intelligence, 5G, biochips, the decentralized web, etc.) are now represented within newer modalities or distinctions. 

It’s also worth noting the impact of the pandemic on the prevalent technologies. 

For comparison, here’s my article from 2019, and here’s my article from 2015.  Click on the chart below to see a larger version of this year’s Hype Cycle.

 

via Gartner

Last year’s themes were:

1. Evolving/Expanding Immersive Experiences,
2. Accelerated Artificial Intelligence Automation, and
3. Optimized Technology Delivery (digital businesses)

This year, the key technologies were bucketed into four major themes.

• Emergent AI represents the technologies that increase workforce productivity and differentiation from competitors.  The hallmark technology of this theme is Generative AI, but another exciting one is AI Simulation - where environments and people can be replicated virtually to run simulations and ask questions.  Imagine being able to create a digital replica of yourself (or a specialist in different disciplines) to bounce ideas off of ... or to create a virtual advisory board to help process tough issues or test the response to various situations, opportunities, or challenges.
• Developer Experience (DevX) is precisely what it sounds like.  Enhancing the developer suite of technologies not only enhances your engineering team but also helps attract and retain high-level employees.  Value Stream Management Platforms (VSMP) is a good example of this.  VSMP is intended to optimize product delivery from end to end. 
• Pervasive Cloud focuses on how cloud computing is evolving.  This theme is also focused on creating an end-to-end use case.  In an ideal world, this enables easy and automated operational scaling, lots of cloud-native tools, and stability improvements.  A sample technology under this umbrella would be WebAssembly, a lightweight virtual machine and binary code format that would enable secure, high-performance applications on your web pages. 
• Last but not least, we have Human-Centric Security and Privacy.  In response to growing security concerns, this theme recognizes the pressure companies face to create cultures and systems that value and protect security.  AI Trust, risk, and security management (AI TRiSM) is the culmination of this effort and represents a holistic approach to governance, reliability, efficacy, and more.  This will be an important frontier to develop as we innovate faster. 

Last year, the main focus was on the spread of emerging technologies.  Last year’s themes focused on the ubiquity of AI in all facets of life – and the increasing immersiveness of these technologies. 

This year, the focus seems to be on responding to that increasing ubiquity.  It’s about building systems that help adopt these new technologies efficiently ... while also protecting yourself from making mistakes at lightspeed. 

Of course, I’m always most interested in the intersection of AI and other spaces.  Last year, AI became a lighthouse for businesses to work toward.  It’s continued to shine a light this year.  In my opinion, this points towards the increasing maturity and adoption of AI.  The opportunity cost of adopting AI into your business is continuing to decrease.

Meanwhile, these systems are also becoming more autonomic, self-managing, and self-learning.  I’m excited to see Gartner emphasizing what this does for humans - not what it takes away from them.  Remember, the heart of artificial intelligence is human - and it continues to free us up to be more human.  

 

As we reach new echelons of AI, you’ll likely see increasing examples of over-hype and short-term failures.  You often miss a rung on the ladder as you reach for new heights, but it doesn’t mean you should stop climbing.  More importantly, it doesn’t mean failure or even a lack of progress.  Challenges and practical realities act as force functions that forge better, more robust, resilient, and adaptable solutions that do what you want (or something better).  It just takes longer than you initially wanted or hoped.

To paraphrase a quote I have up on the wall in my office from Rudiger Dornbusch ... Things often take longer to happen than you think they will, and then they happen faster than you thought they could. 

Many of these technologies have been hyped for years - but the hype cycle differs from the adoption cycle.  We often overestimate what we can do in a year and underestimate what we can do in ten years. 

I say it often ... we live in interesting times!

Which technologies do you think will survive the hype?

Let me know what you think.

Onwards!

Camp Kotok: Back Again!

I was just in Maine at Camp Kotok, a private gathering of economists, fund managers, and other financial industry professionals. 

There was limited phone service or access to the Internet… so people had to talk with each other.  And unlike most of my schedule, almost everything happened outside.  Discussions, while vigorous, often take place while fishing or grilling. 

At a past Camp Kotok, I did this interview with Bob Eisenbeis, Cumberland Advisors' Vice Chairman & Chief Monetary Economist.  Check it out. 

 

Cumberland Advisors via YouTube

 

Camp Kotok is an interesting place. The event transformed from a simple retreat after 9/11 ... when many attendees experienced the WTC collapse and came together for some fellowship and to discuss their experiences.  From then on, attendance grew, and the gathering evolved. 

As a side note, before the gathering became known as Camp Kotok, it was referred to as the “Shadow Fed” (in part because of the people who attend).

Attendees are bound to “Chatham House Rules” (participants are free to use the information received, but neither the identity nor the affiliation of the speaker(s), nor that of any other participant, may be revealed).  However, general thoughts, ideas, forecasts, and comments can be discussed and published.

On this trip, I talked with David Kotok about the event, what it means, and how it’s grown.

The intent of the participants (and the environment) helps create a platform for meaningful and productive conversations about the opportunities and obstacles facing America and the world. 

Every year, I come back with new ideas and fresh perspectives on things I forget to think about. 

AI was on everyone's mind.  The financial industry is changing quickly, and I’m confident that advanced technology will become an even bigger driver. 

In general, economically, the mood was cautiously optimistic to bullish. 

Remember, it is an election year!

"Is The Stock Market Going To Crash?!"

I usually don't concern myself with looking at stock charts anymore, but I still like paying attention to what people say about them ... 

Recently, I saw this image posted.

via r/StockMarket

So, will the market attract buyers … or sellers?

Personally, I expect volatility.  

Why?  

Because markets exist to trade, and it tends to generate those trades by 'shaking' the weak holders.  

A big move up here will trigger a lot of buying (and short-covering by weak bears).  

While a big move down will trigger a lot of selling (as Bulls fear the long-anticipated next leg down).

I also recognize that we're entering an election year. So there's still time for a correction before a sustained rally.

Here's the problem.  Even though I still enjoy the mental exercise of going through these scenarios, I recognize how little value they add.

You can look at any point in history and find articles and charts that tell you the world is ending, or that the fear is overblown and we're going to get to the other side, and there's a pot of gold waiting for you. 

It's easy to use charts to explain what happened. It is a lot harder to use charts to predict what is about to happen.

I still keep my ear to the ground because I like having a feeling for the sentiment around both experienced investors and your average Joe.  Conventional trading wisdom says that crowds are usually wrong at turning points.  That doesn't mean they are always wrong (still, it makes sense to notice when Smart Money clearly disagrees). 

Knowing these things doesn't make any difference in the decisions I make about trading ... because I let the computer make those decisions.  Nonetheless, it makes me feel better. 

So, is the stock market going to crash?  Who knows?  Anyone that pretends they know is full of it.  There are too many factors at play to decide whether the market is going to crash.

From my perspective, it doesn't make sense to try to predict something random.

On the other hand, if you don't know what your edge is ... you don't have one.

Algorithmic trading is about creating more ways to win. 

To be effective, algorithmic trading is about switching from lower expectancy positions to higher expectancy positions.

In general, here is how that works.

Understand that you can make trading decisions based on market patterns, trends, sentiment, statistics, behavioral economics, game theory, reversion to the mean, or countless other methods.  Further, realize that no technique works all the time ... but there is always a technique that works (even if that means getting out of the market). 

There is an advantage in tracking each of these to gain a perspective of perspectives (in order to identify an advantage or opportunity in real-time as it happens). For example, you could measure and calculate a blend of your confidence in an algorithm or technique and how it is performing.  This creates the opportunity to switch into and out of various techniques and markets as things change.

Having an edge in trading often comes down to information asymmetry. This means knowing more, faster, better, or different things than what others are using to make decisions.

Hope that helps.

Understanding Industrial Revolutions

Last week, I talked about the potential for room-temperature superconductors. 

In that discussion, I noted that we are now in the 4th Industrial Revolution, in part because of better and more connected chips (semiconductors).

I want to dive back into Industrial Revolutions because we're at an inflection point in AI and chips. 

A Look at Industrial Revolutions

The Industrial Revolution has two phases: one material, the other social; one concerning the making of things, the other concerning the making of men. - Charles A. Beard

There are several turning points in our history where the world changed forever.  Former paradigms and realities became relics of a bygone era. 

Tomorrow's workforce will require different skills and face different challenges than we do today.  You can consider this the Fourth Industrial Revolution.  Compare today's changes to our previous industrial revolutions. 

• First industrial revolution - Discovery of the steam engine and creation of factories
• Second industrial revolution - Introduction of the assembly line and mass production
• Third industrial revolution - The world wide web and computers connect the world, enabling the digital age. 

Each revolution shared multiple similarities.  They were disruptive.  They were centered on technological innovation.  They created concatenating socio-cultural impacts.

Since most of us remember the third revolution, let's spend some time on that. 

Here's a map of the entire "internet" in 1973. 

Reddit via @WorkerGnome.

Most of us didn't use the internet at this point, but you probably remember Web1 (static HTML pages, a 5-minute download to view a 3Mb picture, and of course ... waiting for a website to load over the dialup connection before you could read it).  It was still amazing!

Then, Web 2.0 came, and so did everything we now associate with the internet; Facebook, YouTube, ubiquitous porn sites, and Google.  But, with Web 2.0 also came user tracking and advertising, which meant that we became the "product."  Remember, you're not the customers of those platforms - advertisers are.  And if you're not the customer, you're the product.  And when you're not the customer, there's no reason for the platforms not to censor what you see, hear, or experience to control the narrative. 

Now we're seeing a focus on the Blockchain, and its reliant technologies, with Web3.

Where we are and where we are going

I believe that, if managed well, the Fourth Industrial Revolution can bring a new cultural renaissance, which will make us feel part of something much larger than ourselves: a true global civilization. I believe the changes that will sweep through society can provide a more inclusive, sustainable and harmonious society. But it will not come easily. – Klaus Schwab

With Web3, A.I., better chips, and more, we're at the apex of another inflection point.  As a result, the game is changing, as are the rules, the players, and what it means to win. 

At significant transition points, it is easy to see fear, resistance, and a push to keep things the same.  Yet, time marches on.  Much of the pain felt during these transitions occurs because people hesitate to adapt.  As a result, the wave crashes on them instead of them riding it to safety. 

Robots can do many things, but they've yet to match humanity's creativity and emotional insight.  As automation spreads to more jobs, the need for management, creativity, and decision-making won't go anywhere … data and analytics might augment them, but they won't disappear. 

Our uniqueness and flexibility rightly protect our usefulness.  AI and automation free us up to be our best selves and to explore new possibilities. 

All of these changes bring about a decentralization of power - and a new set of freedoms for people – including the ability to discover and adopt capabilities in less time and with less effort.  But, to bring it back to my skepticism again, there are a lot of roadblocks, interferences, and time between now and the consumer being in control again. 

We can shorten that distance, though.  This reminds me of a quote by Elon Musk: 

Stop being patient and start asking yourself, how do I accomplish my 10 year plan in 6 months? You will probably fail but you will be a lot further ahead than the person who simply accepted it was going to take 10 years."

One of an entrepreneur's most powerful capabilities is the ability to shorten time - and get more done than others thought possible. 

Onwards!

Are You Ready For Some Football?

Are you ready for some Football?

Yesterday was the Cowboys' first preseason game. 

It wasn't exactly the prettiest (partly because it was the first game of the season, but also because many of the starters sat the game out to avoid injury).  With that said, it was still a fantastic experience.  The NFL (and Jerry Jones) knows how to put on a show. 

 

It's Easy to Feel Good at the Start of a Season.

Lots of people ask me how the Cowboys look this year.  The truth is, at this point in the season, it's impossible to know because injuries have a dramatic impact on the game.  

Regardless, each year I choose to be optimistic about the chance of a post-season run. 

That kind of logic (or lack there of) is why I think automated trading is better than humans attempting to do it themselves.  It's a way to make objective decisions and eliminate fear, greed, and discretionary mistakes.

On the other hand, it feels so good to hope!

A Lesson From the Game.

I had an interesting discussion at the game yesterday.  My guest commented that Jerry Jones is a fantastic business person - which is hard to argue - but probably shouldn't be running the team.  He believes the team needs a change of pace to switch things up. 

While I don't know if that's why we tend to struggle so much more late in the season, it reminded me of a great business lesson. 

Entrepreneurs often mistake their domain expertise for general expertise.  "I'm fantastic because I'm fantastic at all these different things." And the result is they overestimate their ability to be great at things outside their unique ability.  A similar issue is that many people believe they are deep thinkers, because they think deeply about what they think about.  However, they often don't realize how narrow their range of thinking is, and how many things fall outside their expertise, interest, or even consideration.

Less Is Often More.

Learning to offload tasks that you may not be as fantastic at as others is a great way to free up time to focus on not only the things that you're great at – but also bring you joy and energy. 

Hope that helps!

How 'bout them Cowboys!

A Brief Look At Quantum Computing

I am not an expert on quantum computing ... but I saw an impressive photo of Google's new quantum computer, and thought it was worth diving a bit deeper. 

Google's computer stands at the forefront of computing technologies. This extraordinary device boasts 70 qubits, a significant improvement over the previous 2019 model, which had 53 qubits. A qubit is the quantum world's answer to classical bits. Not to dive too deep, but as you increase the number of qubits in a model, the possible states a quantum computer can hold simultaneously grows exponentially (due to quantum entanglement,) allowing it to perform faster calculations.

So, while 70 qubits don't sound like that much, it calculates exponentially faster than normal computers. For some context, Google's team used a synthetic benchmark called random circuit sampling to test the system's speed, and the results showed that they could perform calculations in seconds that would take the world's most powerful supercomputer, Frontier, 47 years. 

Four years ago, Google announced that they'd reached quantum supremacy, a benchmark demonstrating that a programmable quantum device could solve a problem impossible for classical computers to solve within a practical timeframe. It took less than five years to successfully establish the technological feasibility of quantum computers. 

The progress made in quantum computing enhances our capacity to tackle complex problems that previously posed a challenge (or seemed impossible). The ripple effects will extend to other domains and industries (improving artificial intelligence, logistics, medicine, and almost anything you can imagine). As with the space race or AI, the benefits will not be limited to the realm in which they were created ... but will also have a significant impact on broader industries, the world, and our lives.

 

It's important to temper your expectations and recognize that quantum technology is still in its infancy. It comes with significant limitations, such as the need for extremely low temperatures and precise magnetic fields. Even if these specific conditions are satisfied, there will be stability issues. Additionally, the current cost to develop and operate this technology is quite high.

But, it's an exciting horizon for us to walk towards. 

Onwards!

Here Are Some Links For Your Weekly Reading - July 9th, 2023

Here are some of the posts that caught my eye recently. Hope you find something interesting.

Lighter Links:

• France Set to Allow Police to Spy Through Phones. (Lemonde)
• Your Most Ambivalent Relationships are the Most Toxic. (NYT)
• Is Positive Psychology Science or Snake Oil? (PsychologyToday)
• Einstein and Musk Chatbots Are Driving Millions to Download Character.AI. (Bloomberg)
• New Report Warns of Brain Control Weapons Being Developed by Communist China. (DailyWire)

Trading Links:

• The Copyright Battles Against OpenAI Have Begun. (Quartz)
• Baby Boomers Own Pretty Much Everything - But Millennials Could Be About to Catch Up. (Markets)
• Forbes World's Billionaires List 2023: The Top 200. (Forbes)
• Wall Street Soothsayers Are Bewildered About What's Next. (Bloomberg)
• SVB, BBBY, Lordstown Lead List of US Bankruptcies as Companies Fold up at the Fastest Pace Since 2010. (Markets)

Economic Allies and Economic Enemies

Last week, I brought up the concept of Economic Freedom. It reminded me of an idea I last shared in 2008, during the housing crisis. 

I noticed how correlated and coordinated worldwide actions were during the housing crisis. During the pandemic, while there was a lot of dissent, there was also a remarkable amount of coordination. 

The concept of economic allies presupposes that we also have economic enemies. It’s easy to construct a theory that countries like Russia and China use financial markets to exert leverage in a nascent form of economic warfare.

It's easy to come up with a theory that suggests we are our own worst enemies. Our innate fear and greed instincts (and how we react to them) tend to lead us down a path of horrifying consequences. This has been evident in recent years, not just in society, but also in the world of business. I am confident that this pattern will persist in the context of Artificial Intelligence, with both its potential benefits and risks.

The butterfly effect theorizes that a butterfly flapping its wings in Beijing on one day can create or impact a rainstorm over Chicago a few days later. Similarly, in a world with extensive global communication and where automated trading programs (and even toasters) can interact with each other from anywhere across the globe, it is not surprising that market movements are becoming larger, faster, and more volatile.

Perhaps governments cooperate and collaborate because they collectively recognize the need for a new form of protection to mitigate the increasing speed, size, and leverage behind market movements.

And we can also extend this idea to other entities beyond governments. It doesn’t have to be limited to traditional markets either; it can include cryptocurrencies or other emerging technologies as well.

It’s worth understanding the currents, but we must also consider the undercurrents and countercurrents. 

Conspiracy theories are rarely healthy or helpful, but maintaining a healthy skepticism is a great survival mechanism.

Hope that helps.

The AI Hacking Paradox

Fear is a natural response to change or the unknown, serving as an evolutionary mechanism designed to safeguard us. However, it’s also worth noting that many of our fears turn out to be unjustified.

Sometimes, however, fear is a much-needed early warning system. 

In the context of AI hacking, you should be afraid. Given the exponential growth in technology and artificial intelligence, concerns about security breaches and intentional misinformation campaigns have become common.

In 2016, DARPA created the Cyber Grand Challenge to illustrate the need for automated, scalable, machine-speed vulnerability detection as more and more systems—from household appliances to major military platforms—got connected to each other and the internet. During this event, AI systems competed against each other to autonomously hack and exploit vulnerabilities in computer programs. The competition revealed the unprecedented speed, scope, scale, and sophistication with which AI systems can find and exploit vulnerabilities.

And that was seven years ago. 

AI hackers operate at superhuman speeds and can analyze massive amounts of data, enabling them to uncover vulnerabilities that might elude human hackers. Their ability to think differently, free from human constraints, allows AI systems to devise novel hacks that humans would never consider. This creates an asymmetrical advantage for AI hackers, making them formidable at infiltrating and compromising systems.

We expect people to use AI for malicious purposes intentionally, but unintentional AI hacking arises when an AI autonomously discovers a solution or workaround that its creators did not intend. This type of hack can remain undetected for extended periods, amplifying the potential damage caused. 

So, how do we stop it?

Ironically, or perhaps, exactly as you would expect it, AI itself holds the key to defending against future attacks. Just as hacking can drive progress by exposing vulnerabilities and prompting improvements, AI hackers could potentially identify and rectify weaknesses in software, regulations, and other systems. By proactively searching for vulnerabilities, they can contribute to making these systems more hack-resistant. This is the paradox of AI hacking. 

It’s the same concept as I mentioned in the article on potentially halting the creation of generative AI.  

Unfortunately, when you invent the car, you also invent the potential for car crashes ... when you ‘invent’ nuclear energy, you create the potential for atomic bombs. That’s not a reason to stop innovation - it’s a call to action for innovators to respond faster and counteract the bad actors. 

We can’t stop bad actors from existing - but we can get better at preventing harm due to them. This is a helpful framework for innovation. If you want to stop the bad actors from misusing a technology, the good actors "simply" have to get better at using the technology faster. 

The best way to stop negative motion is with positive motion. But, we can also make moves in the background to counteract bad actors and bad actions.

For example: 

1. Regulation and Transparency: Regulatory frameworks can be established for AI technologies that demand transparency regarding how they function and how they’re secured.
2. Ethical Guidelines: Implementing ethical guidelines for AI development can help prevent misuse.
3. Cybersecurity Measures: Enhancing cybersecurity protocols and utilizing state-of-the-art encryption methods could make AI systems more resilient against hacking attempts.
4. Education: Increasing public understanding of AI technologies would spread awareness of their benefits alongside potential risks.

While these measures won’t eliminate the potential risk of AI hacking, they could significantly mitigate it and provide reassurances about employing such technologies.