Sten Vesterli's Blog

Making IT Live up to its Promise

Category: Technology That Fits

The ROI on AI Projects is Still Negative

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Unless you are Microsoft, your IT solutions are expected to provide a positive return on the investment. You might have heard that Microsoft loses $20 a month for every GitHub Copilot customer. That’s after the customer pays $10 for the product. If you are a heavy user of Copilot, you might be causing Microsoft a loss of up to $80 every month.

Some organizations are rich enough to be able to afford unprofitable products like this. They typically have to spend their own money. VCs seem to have soured on the idea that “we lose money on every customer, but we make up for it in volume.”

If you are running an AI project right now, you should be clear that it will not pay for itself. Outside a very narrow range of applications, typically image recognition, AI is still experimental. If you have approved an AI project based on a business case showing a positive ROI, question the assumptions behind it. The AI failures are piling up, and even the largest, best-run, and most experienced organizations in the world cannot make money implementing AI yet. You probably can’t, either. Unless you have money to burn, let someone else figure out how to get AI to pay for itself.

AI is not Coming for Your Job

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Unless you write corporate mission statements, AI is not coming for your job. Generative AI like ChatGPT works by continually adding the most likely next word. That ensures that an AI-written text is a bland average of all the texts it has read. It is unlikely to be thought-provoking or even useful.

I was reminded of how useless an AI-generate text is when LinkedIn invited me to participate in a “collaborative article.” The AI generates a text on a subject, and I am supposed to add a real-life story or lesson next to that. Unfortunately, the AI text is a collection of trivial platitudes. LinkedIn asked me to rate the article, and I immediately clicked “It’s not so great” (because there was no lower rating). Unfortunately, the feedback options did not include “Your AI text adds no value.”

The striking writers in Hollywood want guarantees from the studios that they won’t be replaced with AI. They need not worry. A script written by AI will be mind-numbingly boring. What AI might do for the film and TV industry is to take over boring housekeeping tasks like ensuring continuity – was the blood on his left or right jacket sleeve? But it won’t write the next hit show or movie.

The right way to use AI in its current state is to use it deductively – to analyze stuff. Programmers who inherit a huge pile of undocumented code benefit from having ChatGPT or its siblings explain the code. Using AI inductively to generate text might be fun, but it doesn’t create any value.

The Guard Rail Pattern

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There is a simple way to prevent many IT disasters, and it is sadly underused. It’s not on the standard lists of design patterns, but I call it the “Guard Rail” pattern.

It would have prevented the IT disaster that dominates the news cycle in Denmark these days. Techno-optimists have forced a new digital building valuation on the long-suffering Danes, and it is an unmitigated catastrophe. The point is to replace the professional appraisers who determine the value of a property for tax purposes with a computer system. And many of the results from the computer are way off. Implementing a Guard Rail pattern would mean that the output from the new system would be compared to the old one, and those valuations that are, for example, 3x higher would be stopped and manually processed.

A colleague just shared a video of the latest iteration of the Tesla Full Self Driving mode. This version seems to be fully based on Machine Learning. Previous versions used ML to detect objects and traditional algorithmic programming to determine how to drive. As always infatuated with his own cleverness, Elon Musk does not seem to think that guard rails are necessary. Never mind that the FSD Tesla would have run a red light had the driver not stopped it. Implementing the Guard Rail pattern would mean that a completely separate system gets to evaluate the output from the ML driver before it gets passed to the steering, accelerator, and brakes.

When I attach a computer to my (traditional) car to read the log, I can see many “unreasonable value from sensor” warnings. This indicates that traditional car manufacturers are implementing the Guard Rail pattern, doing a reasonableness check on inputs before it passes the values to the adaptive cruise control, lane assist, and other systems. But the Boeing 737 MAX8 flight control software was missing a crucial Guard Rail, allowing the computer to override the pilot and fly two aircraft into the ground.

In your IT organization, discuss where it makes sense to implement the Guard Rail pattern. Your experienced developers can probably remember several examples where Guard Rails would have saved you from embarrassing failures. There is no need to keep making these mistakes when there is an easy fix.

AI Will Not Destroy Humanity

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AI doesn’t pose an extinction risk. And it has already created brand new jobs in the catastrophizing industry.

The only reason AI industry leaders like Sam Altman and Demis Hassabis jump on that bandwagon is to encourage more government red tape. If you are a powerful incumbent, asking for as many constraints to your industry as possible makes sense. The EU, ever happy to regulate industries originating elsewhere, is delighted to oblige. With compliance departments of thousands, these massive organizations can handle any amount of regulation thrown at them. But a lean startup will get regulated out of business.

The most fascinating part of AI is local, small-scale AI. We currently have massive, centralized AI running in enormous data centers. But since LLaMA escaped from the Facebook lab, tinkerers and hobbyists have already built Large Language Models on their local computers. But, of course, OpenAI, Microsoft, and Google would like small competitors to be regulated away.

Did You Hear the One About the Gullible Lawyer?

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You need the best arguments to win a discussion, get a project approved, or win a court case. But, if you are short of preparation time, you might take a shortcut like the New York Lawyer who asked ChatGPT for help.

Ever willing to help, ChatGPT offered six cases supporting the lawyer’s argument. Unfortunately, they were entirely made up. That might work if you write a marketing blog post, but it does not hold up in court. The gullible lawyer claims he did not know that ChatGPT might be hallucinating but is, of course, facing sanctions for lying to the court.

IT professionals know that ChatGPT cannot be trusted to answer truthfully. It is not much of a problem for a programmer because the compiler or the unit tests will catch defective answers. But the rest of the world doesn’t know.

Now is the time to remind everyone in the organization of your company policy on using ChatGPT and its ilk (you do have such a policy, right?). Tell the story of the gullible New York lawyer to make the point clear.

Cloud Means Aomeone Else is in Control

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Cloud services mean you are at the mercy of someone else. It is bad enough that hackers broke into Western Digital’s My Cloud service and encrypted their customer’s data. But many private customers are now learning what it means to use WD’s cloud-based login service. It means that even though your data is stored on your own NAS device in your own basement, you still cannot get at it when WD is down.

If you are using any cloud-based login service in your organization, ask your CISO how people would log in and access ressources if that service is down.

Where is the Profit

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“But we’re a startup!”

“That’s not enough anymore. How will you become profitable?”

This is the essence of discussions between startups and their VC funders today and increasingly between big companies and their shareholders. Unfortunately, Ford’s CFO didn’t get the memo because he is still trying to pass off their $3 billion loss on electric vehicles with the “consider-us-a-startup” excuse.

Increased shareholders’ attention is also forcing all the big tech companies to kill off many of their loss-making projects that do not have any path to profitability, with an accompanying bloodbath of firings.

An audit showed that 47 of the 98 Danish municipalities were running AI projects. Two of these had provided value.

Do you have realistic business cases behind your projects? Or is the business case a collection of rosy assumptions retrofitted onto a project someone just wanted to do? It is better to find and kill vanity projects than to be called to the CEO’s office to explain why you are frittering away the company’s money. Contact me if you want an independent outside opinion on your project portfolio.

Once you Grow up, you Need to Stop Moving Fast and Breaking Things

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Moving fast and breaking things can be fine for a startup. They might need to iterate several times and maybe even pivot once or twice before they achieve product/market fit. It is not OK for an established business. Facebook has long since given up on this strategy, but Twitter, under Elon Musk, has rediscovered it. By thrashing around and changing direction daily, they are alienating both the users and the advertisers who were supposed to pay. If you want to move fast, roll out changes to a small percentage of your users. A mature continuous delivery organization practices blue/green deployment, but even if you are not doing CI/CD, you can still test changes with a small subset of your users. Don’t uncritically inflict the latest great idea on your entire user population. #itleadership #innovation #makeitliveuptoitspromise

Beware of Asymmetric Risk/Reward Profiles

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Would you continue to sell a lock based on technology that has been known for 14 years to be trivially easy to hack? Of course not! But Scantron in Denmark has merrily been foisting insecure locks on unsuspecting Danish apartment administrators. Even after a worried renter told them about the problem in several emails and even physical letters (!), they ignored the problem. It took a media shitstorm to make them realize the errors of their ways.

Digital locks have an asymmetric risk/reward profile. The reward is small – you save a little by not having to administer physical keys and re-key locks. The risk is huge – someone might copy a key, turn it into a master key, and rob hundreds of apartments.

When you are evaluating digitalization projects, be very careful about those with such an asymmetric profile. Almost every organization has digitalization projects with a better risk/reward balance than digital locks…

IT Leadership has to Harness the Power of AI

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AI has finally gotten really useful inside the IT organization. Most of the examples on the internet are frivolous and amusing, like how to remove a peanut butter sandwich from a VCR, written in the style of the King James Bible. But ChatGPT is helpful for mundane tasks in IT as well.

I’ve been fixing open issues in a small open-source project recently. One of the issues was that part of the code would concatenate strings to build SQL statements. That’s a classic SQL Injection vulnerability. ChatGPT can fix these bugs faster than I can. So I tell the AI, “please rewrite the following to use bind variables,” and give it the code.

Another example is working we legacy shell scripts. My sed/awk skills are rusty, but I can give a convoluted shell statement to ChatGPT, and it will patiently explain all the options and exactly how it works.

Many of your programmers are already playing with ChatGPT, GitHub Copilot, and other AI tools. You might as well embrace it. Set up a knowledge-sharing community for those curious about how AI can help IT. Have them present to you and the rest of the IT department. You’ll be amazed if you haven’t played with ChatGPT and its ilk.