Reviving a Nikon EN-EL18d with an MH-33: Frankenstein Style
On December 8, 2025 by
Warning: Attempt this at your own peril.
While busy with class this past term, I accidentally let the battery in my Nikon Z9 run down. Usually, batteries are only mostly dead, and will charge back up. This one was beyond mostly dead. Nikon’s charger failed to recognize it at all, and it will blink furiously to let you know that you should immediately go to their website and purchase a new battery for $249. I had already done this a few months prior, and pulled out a spare (still in the box) only to find it, too, was entirely DOA – refusing to charge.
Most, if not all, Li-Ion chargers look for a small charge coming from the battery before it will recognize them. This helps prevent fires and electrocution from people doing dumb things, like putting the wrong battery on the charger, or sticking their tongue on the contacts Christmas Story style. The Nikon MH-33, however, seems to be designed for one purpose: to sell more batteries. It seems to deliberately be built with poor tolerances for the range of voltages that it will recognize on, with a minimum somewhere around 7.5v. If your battery is anything resembling “pretty dead”, you’re stuck buying new overpriced batteries. Or are you? If you can get the charger to recognize the battery, it can often be revived.
XGecu T76 on Windows 11 ARM
On November 27, 2025 by Jonathan Zdziarski
Running the XGecu T76 chip programmer with x86 emulation has been miserably slow, even on my M4 MacBook Pro, and so I finally took some time to figure out how to get it working on Windows 11 ARM in Parallels on Apple Silicon. There wasn’t any information online about this, except for one person who had some luck with Zadig, but had no idea what they actually did. I’ve documented the entire process below, which works with or without Zadig; the key is not only changing the driver to a native WinUSB driver, but also correcting some crucial GUIDs in the registry to ensure driver matching works in the software. For this, I’ve created a simple registry file that can be easily imported.
Essays . Machine Learning . Opinion
The AI Learning Plateau
On November 2, 2025 by Jonathan Zdziarski
There’s an old 1985 sci-fi series I remember watching as a kid. In Otherworld S1E1, the Sterling family, on vacation in Egypt, winds up in a parallel dimension where they encounter a civilization of self-evolved AI androids. Parts of the episode were amazingly spot on to how today’s LLMs are playing out. In the episode, the teenage son (Trace) falls in love with an AI, and the android itself is entirely convinced she not only has a soul, but is genuinely in love with him too. While this android city looks relatively human-like, and performs similar tasks (such as eating, working, etc), the show highlights some peculiarities where they’ve attempted to copy human behavior, but failed in eerie ways. One of my favorite scenes is where the Sterling family matriarch (June) visits the grocery store in this strange civilization, and finds only cans labeled, “Meat” and “Good Food”. The AI world seemingly lacked a crucial connection with humanity to develop creativity beyond a superficial level. The insults that robots cast at each other were humorously corny, such as “get your unit checked!”; when they asked if you were born yesterday, they literally meant it because that’s all they understood.
Arcade Board CAD Files Now Available
On October 17, 2025 by Jonathan Zdziarski
Now that I’ve cleared the appropriate IP hurdles with my employer, I’m able to make the CAD files available for the arcade boards I’ve blogged about recently. Included in this repo are adapters for:
- Atari Multi-System JAMMA Edge
- TRON / Discs of TRON
- RoadBlasters
- Spy Hunter
- Universal JAMMA Edge
- Williams Multi-System JAMMA Edge
- New: Arduino-Compatible Microcontroller Edges (Atmel 328)
I haven’t blogged about the Williams interface, however it is essentially a universal edge with a signal combiner, op-amp, and -12V boost inverter to support Williams games. I’ve Joust and Defender running on it at home quite happily.
All of these CAD files are for educational use only.
Repository URL: https://github.com/jzdziarski/jamma/
Arcade Hardware Hacking: Part III
On October 7, 2025 by Jonathan Zdziarski
Spy Hunter (Steering Yoke, Gear Shift Latch, and Lamp Conversion)
Arcade Hardware Hacking: Part I
Arcade Hardware Hacking: Part II
Spy Hunter is a well loved classic, and by far the most challenging and ambitious title I have worked on to date. While the purists will insist that the only way to enjoy the game is on the original arcade hardware, many (many!) adaptations to various consoles have been met with incredible success. My goal was to adapt the original arcade version of this to work on my coffee table with a JAMMA super-gun, or in a JAMMA multi-cabinet that wouldn’t necessarily have a dedicated steering yoke or pedals. To accomplish this, Spy Hunter comes with many new challenges over and above other games I’ve adapted:
- The MCR board uses a daughter board to obtain readings from potentiometers for both the steering wheel and accelerator. Unlike TRON’s spinner, these controls are entirely analog and are read into absolute values using an ADC (analog-to-digital converter). There is one data “bus” (a shared, physical pathway) sharing inputs ultimately into the MCR board for both steering and accelerator, and the value being read is determined by a separate pin on the main board (which enables the corresponding analog input). In the digital world, both values remain in state and depending on what the main board calls for, you must provide the correct value to the pins.
- One of the more ingenious ways to avoid piracy, Bally/Midway used a lamp panel to display the weapons available to the player at any given time, along with a flashing lamp indicating when the weapons van could be summoned. Along with the steering controls, this helps bind the software to the hardware of the cabinet. Without this lamp panel, the user has no idea when they can call the weapons van (unless they see it parked by the side of the road), what weapons they have readily available, or if they’ve expended them. A lamp driver reads the latches set by the game and illuminates the correct bulbs.
- The board has two separate audio channels, one for effects and one for music. A daughter board named the “Cheap Squeak Deluxe” plays the Peter Gunn theme (which was supposed to instead be the James Bond theme, but Midway couldn’t obtain the licensing). Sound is mixed across two separate amplifiers in the sit down version of the game. I’ll have to merge four audio channels (L and R) into a single mono channel suitable for JAMMA.
- An accelerator pedal must somehow be adapted to controller buttons. This is a somewhat sensitive problem, as nuanced work with the pedal is key to playing the game well.
- The gear shift is a physical stick that shifts between high and low. This, too, will need to be adapted to modern controls. I’ll end up doing this in the form of a toggle.
- In addition to emulating all of this, the adaptation must somehow be easy to play with a controller or joystick. I’m using a BlueRetro Bluetooth adapter with a Nintendo Pro Controller, so with use of the extension harness, I’ll have six buttons at my disposal.
Arcade Hardware Hacking: Part II
On August 30, 2025 by Jonathan Zdziarski
RoadBlasters (Steering Yoke Conversion)
Arcade Hardware Hacking: Part I
Arcade Hardware Hacking: Part III
Temple of Doom was a great introduction to the Atari System 1 logic board, and as it turned out was very easy to adapt to the JAMMA standard. With the exception of inverting the directional buttons (and the ridiculous number of repairs I had to make to the board), everything was super straight forward and amounted to simply mapping pins on the logic board to JAMMA pins with the help of the schematics. But Temple of Doom isn’t the only great game released on this platform. System 1 is a modular platform; Atari was able to save a lot of money by shipping out new cartridge PCB kits to arcade owners. These kits typically came with a new marquee and control panel so if you already owned an Atari System 1 cabinet, you could swap out games pretty easily without having to freight an excessively heavy cabinet. Once games lost popularity, they were just dead space in the arcade. This cost square footage, and also a great deal of electricity to run all day. Atari’s approach to game refreshes (which predated JAMMA by a few years) made it easy for arcade owners to save money and space. The System 1 supported a handful of games including Temple of Doom, Marble Madness, Road Runner, and the focus of this post: RoadBlasters.
RoadBlasters was one of my favorite racing games (next to Outrun, which will forever be crowned the best), and was also a System 1 platform game. Unlike Temple of Doom, there’s no joystick. The controls are very nuanced, as they are with many arcade racers, and included a steering yoke and foot pedals. You can imagine this was handled very differently electronically than a racer you’d play on, say, NES (like Rad Racer, which I grew up on). It’s not a very popular game for home arcades because you typically need to own the original steering yoke (or a compatible aftermarket one, if such a thing exists) in order to play it, which means a dedicated machine or something hacky. I’ve always found at-home steering wheels and pedals a bit dumb anyway, and prefer playing a racer with a gamepad or joystick. I’m certainly not going to buy some old arcade yoke (or a complete cabinet!) just to play a game. They’re charging some stupid prices for these too, because they can.
Arcade Hardware Hacking: Part I
On July 28, 2025 by Jonathan Zdziarski
Temple of Doom and TRON to JAMMA Conversion
Arcade Hardware Hacking: Part II
Arcade Hardware Hacking: Part III
I’ve been dabbling a bit in amateur EE this summer as my interest in rehabbing arcade games has recently hit a peak. It started with this 40-year old trashed Indiana Jones: Temple of Doom Atari System 1 board I found for cheap. If the seller says, “was working last time I played it, but don’t have the ability to test it now”, that’s code for “I backed over it with my car”, and “it’s trashed and I need plausible deniability for financial reasons”. Nevertheless, it’s a pretty rare find and was one of the three arcade games I remember playing with my dad at the pizza joint before he got too sick, so the game has a lot of sentimental value. Even broken, a complete System 1 with IJ board was a steal for a few hundred bucks. Over the course of a few weeks and hours of reading through schematics, I identified and replaced a total of 11 bad ICs – probably the result of a past power surge. I finally got it running 100% after fixing a whole laundry list of things: sprites, audio, VRAM, NVRAM, speech synthesis, FM synthesis, multiplexers, and address lines.
JAMMA. Why’d it have to be JAMMA.
JAMMA is an industry standard for arcade games, introduced to make it easier (and cheaper) to swap games and controls out without having to use an entirely different cabinet. It’s also what modern at-home systems (a “Super Gun” or a “Mini Gun”) use to play old video game boards on your own setup at home. A Super Gun interfaces with the JAMMA edge on a game board and supplies the necessary voltages and inputs, and plumbs the video and sound out to something that can be rendered on a monitor or CRT. My Super Gun (I own an Axunworks and a HAS, though I prefer Axunworks) sits on a coffee table in my office with an 18″ 1080p monitor, an OSSC Pro scaler, and four Nintendo Pro controllers using BlueRetro receivers. So as old arcade cabinets continue to rot, fall apart, or be exiled to the basement by now-married man-children’s wives, a conversion to JAMMA means that we can preserve some excellent games, allowing the community to play the boards on a modern TV without needing to keep (and upkeep) the very large wooden cabinets they used to come in – many of which were sadly generic. I usually mount my boards on acrylic to protect them at the front and back; this also lets me manage them like giant cartridges, rather than a stack of PCBs.
Essays . Machine Learning . Opinion
Can AI Compute Empathy?
On March 29, 2025 by Jonathan Zdziarski
Empathy is often defined as understanding another person’s experience by imagining oneself in that other person’s situation: One understands the other person’s experience as if it were being experienced by the self, but without the self actually experiencing it.
Hodges and Myers, Encyclopedia of Social Psychology
Reinforcement Learning is a modern AI technique where a system can learn a sequence of actions leading to the most optimal outcome for itself. It essentially works by giving the AI a set of objectives (and sometimes penalties), and allowing the machine to learn from its own experiences what actions work best at accomplishing the objective. It’s how AIs can teach themselves to play video games, solve complex problems, and perform more sophisticated tasks as well. Reinforcement Learning is likewise one of the more concerning areas where catastrophic value alignment failures can occur. This is because it is largely centered around simplified human abstractions of rewards and penalties. As far as the machine is concerned, its job is to find the most rewarding means of accomplishing a task, with penalties only being considered if they are explicitly enumerated. Yet if control theory has taught us much, it’s that hazards cannot always be sufficiently enumerated.
Essays . Forensics . Machine Learning . Opinion . Security
The Shifting Power Dynamics of AI
On December 22, 2024 by Jonathan Zdziarski
One of the focus areas of my graduate research is artificial intelligence. In my foray into adversarial game theory, I became acquainted with AI’s value alignment problem firsthand. In the development of a strategy-theoretic AI Chess agent project, I decided that it should lose points for allowing its pieces to be in jeopardy. The change resulted in the opposite effect I had hoped – significant losses, which puzzled me at first until I realized that the agent was killing off its pieces to prevent them from being put in jeopardy (once this was worked out, the strategy-theoretic approach dominated all other AI techniques, as it provides accurate non-terminal RL feedback). In the grander context of artificial intelligence, the potential for a catastrophic value alignment failure is all too easy to create as the result of short-sighted policies (such as my Chess strategy), or other simple miscalculations.
It’s in everyone’s best interest for AI to behave rationally, however many believe that – in the context of modern AI and deep learning – AI can never be formally verified to the degree that its actions can be deterministically predicted to be responsible. We tend to treat AI with the same sense of dualism that we treat reality, yet the one thing we do know is that AI is an entirely materialistic universe, and not dualist at all. Determinism of AI systems is based upon pure mathematics, with predictable causation. It is true that we can not always observe why AI behaves a certain way, however here we can learn much from classical Stoicism. The early stoics asserted that all qualitative states are explained by specific factors, even if those factors were not always observable. All subsequent qualitative states are likewise determined by the prior states and additional factors. No change can happen without an explicit cause. Whether it’s the logical determinism built through training data, alignment of real time with processing cycles, or reconciling other factors, every single micro state within a configuration of the machine can be observed with enough work. While modern philosophy essentially rejects the stoic concept of fate (of humanity), “fate” in computation falls square within the realm of an entirely deterministic material universe. AI lives in a material world, and she’s a material girl.
AI is largely unverifiable today because industry hasn’t created an affordable way to provide the computing power to observe all factors that contribute to a system’s qualitative state. Despite the inability to verify AI, industry has plotted a course regardless of edge cases that may sometimes be life threatening. Incredible progress in artificial intelligence has all but guaranteed it will be ubiquitous one day. There is little doubt that autonomous vehicles will eventually outperform human drivers, or that machine learning can more accurately diagnose a health problem. There is, on the other hand, great doubt that industry will act responsibly enough to ensure sufficient safety controls intervene when things go wrong. AI will likely never operate with rational judgment 100% of the time, nor will it ever understand the ethical implications of its action; they will always be prone to value alignment catastrophe. Of course, humans lack ethics and rationality as well, and so society controls this by holding us accountable for our actions. Unlike humans, however, industry is treated differently. This is particularly true with emerging technologies and even more so of those that we don’t fully understand. After all, how can one hold math accountable? Dismantling a broken robot does not solve the problem, particularly if the code is replicated across a million others. The connection between what holds true in a computer system and the outcome that is “fated” to occur is “based on an ontological foundation in which certain elements from logic and physics coincide” [6]; Chrysippus wrote of the close relationship between “what is true” and “what is in motion” long before AI in his Bivalence theory. A modern take is simply this: an AI’s “fate” is the direct result of a system’s physical configuration and sensor inputs. Imagine if he were alive to have observed AI, or even a good quality toaster.
The Case for College
On March 13, 2024 by Jonathan Zdziarski
As long as a branch of science offers an abundance of problems, so long it is alive; a lack of problems foreshadows extinction or the cessation of independent development.
David Hilbert, 1900
As a self-educated professional working with the best in the field, I think I’m supposed to tell you that you don’t need college to be successful. My journey has been an unconventional one for sure. Growing up in a dysfunctional home with a schizoaffective and abusive father, surviving high school alone was barely manageable. The notion of college was unconscionable to a depressed teenager from a poor home with no parental guidance or support. Computers have been a part of my life since I was eight, where typing programs from the back of magazines into a Radio Shack TRS-80 took me places far away from my terrifying childhood. The highest level of education I’ve accomplished to date is a GED, after failing out of high school. What turned my trajectory around, second only to my faith, was falling in love with learning. I’ve learned a lot over the course of an ongoing 30-year career, and slowly worked my way up from building PCs and doing sysadmin work into software engineering, forensics, and security. With that has come the opportunity to make a lot of impact along the way that’s touched people’s lives, and a lot of self-education. This is a life I couldn’t have possibly imagined for myself. A great career with one of the best companies in the world, a good living, and the opportunities to make long lasting impact. So why would you need college to do the same, especially when billionaires like Peter Thiel are willing to pay you six figures to drop out?
Thiel’s plan for you is a short-sighted one, and doesn’t take into account the difficulty you’re likely to face as a result of taking his offer. What’s missing from Thiel’s story – and all of his romanticized notions- is all the hard from taking this path. Not just the financial hard that it takes, but the hard of navigating an unforgiving world without a degree – regardless of your intelligence. The hard in trying to make meaningful contributions to the scientific community and touch government sectors without a formal education. The difficulty of the mind in grasping for solutions to complex problems but lacking the theoretical foundation to connect with your higher-level knowledge, and the sense of feeling stupid for decades because of it. The hard in having to constantly prove you’re a better choice than the other candidate with a pedigree, no matter what level of experience you have in your field. Sure, you’re not me – I get that, but perhaps consider some of my experience spanning a tech career before you decide to quit school.
Good Medicine for Imposter’s Syndrome
On July 21, 2023 by Jonathan Zdziarski
Much of what we perceive about others in the workplace is their performatory character – what others are inviting you to believe about themselves; it’s an attempt to become the idealized version of ourselves by acting the part. Most of us are very competent in the field, but even still everyone gets imposter’s syndrome from time to time. For the self-taught professionals in tech, it can be the dead body we keep dragging around with us even while making advancements in the field. Some university graduates, too, have struggled with this decaying corpse that plagues the tech world. Left unchecked, it often leads to a devalued sense of self, depression, and even triggers other mental health problems – even in those whose performatory character would otherwise make them appear well put together. I got into professional tech work at the age of 16, some 32 years ago, at a small computer shop building PCs. Having never had the opportunities others had to go to college, I’ve had to grow and adapt my skillset over the span of my career. Imposter’s syndrome – and depression – has been along with me for much of my adult life. Even with what continues to be an excellent career at Apple, I’ve struggled with self-worth. Work environments can be nurturing and stimulating, and bring out the best in you; they can also be demotivating and devalue you – imposter’s syndrome can follow you around through both. I’ve figured a few things out about myself over the past 32 years that have helped me navigate some difficult environments. Nobody develops imposter’s syndrome overnight. Any sickness that is chronic requires a long term cure. There’s nothing anyone can tell you that will simply fix imposter’s syndrome; there are incremental ways to slowly recover from it though.
Oxford’s definition of imposter syndrome is the persistent inability to believe that one’s success is deserved or has been legitimately achieved as a result of one’s own efforts or skills. In tech, this usually means we feel stupid because we don’t think we have the understanding or mastery we think we should. It’s interesting, though- people tend to often feel like it’s because they’re not smart enough. We are definitely smart enough to do this job. The reason we don’t have understanding isn’t because we’re missing brain cells. One thing that computer science is good at is abstractions, and that allows us to work with and learn higher level concepts without needing knowledge of the world beneath it. One might say it’s what makes computing so great. Imposter’s Syndrome seems to prey on the benefits afforded to us by abstractions to introduce uncertainties about our abilities. But there is a way to think in such a way that allows for these abstractions to exist, where X can remain unknown and it won’t bother you, but simultaneously see a universe where X fits in.
If you look at a lot of the brightest minds in computer science, there’s a distinguishable acumen about them that goes beyond simply knowing the subject matter. They have a scientific mind; able to not only explain something, but they’re able to theorize and reason about it, and able to analogize. These are the kinds of skills that make for not only a good scientist, but a good engineer. It’s these same qualities that seem most desirable when we measure ourselves up, and often what smart assholes do such a terrible job trying to mimic. But this acumen doesn’t come from reading source code, mentoring by coworkers, or from reading The Imposter’s Handbook. These qualities come from a combination of foundational knowledge, methodical reasoning, and discipline. Things a lot of self-taught people like me don’t initially get a lot of exposure to. What I think a lot of people want to feel is that they are legitimate. That their knowledge isn’t fake or piecemeal, and that they are armed with the discipline to reason, make advancements, and solve complex problems. So here’s the pat on the shoulder: You’re probably very good at the subject matter you’re trained in, and you are no doubt intelligent if you are working in tech. Here’s the hard: The abstractions we work with in computing have allowed us to develop gaps, and those gaps make us feel really dumb sometimes. To treat your imposter’s syndrome, we’ve got to work at this.
AI is Just Someone Else’s Intelligence
On May 4, 2023 by Jonathan Zdziarski
Mechanical arts are of ambiguous use, serving as well for hurt as for remedy.
Francis Bacon
It’s been a long time since I’ve worked in the field of ML (or what some call AI), and we’ve come a long way from simple text classification to what’s being casually called generative AI today. While the technology has made many advances, the foundational concepts of machine learning have remained analogous over time: fitting a line (or plane) to data in n-dimensional space, so that it can predict future data points. ML depends heavily on a large set of training data, which is analyzed to pull out its most interesting and defining features, and this becomes the basis for training a model. The process might involve parsing text, or performing analysis like object identification or analyzing stylistic features in art. Each of these is, in itself, a smaller – but mathematical – process. I experimented with a primitive form of meta-level learning in text classification several years ago, which may help convey the general idea. This identifies “features” of the reference sample being trained. The features this process pulls out can be simple, like words in a document or pixels from a handwriting sample, though today can be more sophisticated “critical patterns” correlated to literary authorship or artistry, such as patterns within art and music composition, sometimes stored in other models. Whatever the content is, the purpose of the training algorithm is to converge patterns and correlations across the data to build a weighted or structured model. The most interesting patterns in the training data influence weights or probabilities, creating a hidden layer: millions of “gears” that converge to compute the most statistically significant outcomes. In this sense, the term “learning” is a bit of a stretch; what’s happening is more along the lines of mathematical transcription of a set of features; adjusting the weights to solve a really big linear equation. Feature selection is one of the key differences between various ML models, and why you have some constructing music, while others render art. The math is pretty consistent – more sophisticated machines like neural nets are typically trained using backpropagation and gradient descent, while other machines such as chat bots and text generators might use weighted Markov models or Bayesian networks. These approaches have been applied to everything from natural language processing and handwriting recognition, to today’s work in genome sequencing and autonomous driving. Still, these traditional forms of machine learning are not much more than a sophisticated pattern recognizer. It is largely a deconstructive process with coefficients and statistical magic.
Today’s generative AI still goes through this type of deconstructive process, but also has a formative element. Where these new approaches excel is in going beyond parsing information into a knowledge base, but now also applying a formative process to that information – what we might conflate with intelligence, but still falls short of what most would consider the result of human reasoning. To present the data in some coherent form, this involves training not just the information, but the many dimensions of that information (such as the number of different contexts a word may be used in), or in the context of constructs and critical patterns of that information (ABBA, or 1-4-5, as very basic examples), enabling it to formulate an output in the pattern of an existing set of learned reference samples. Basic linear math finds where those dimensions intersect, creating context. But even modern training approaches, such as those used in the transformer model, still require supervised testing to tell the model what bits of its output are garbage, so that the output eventually looks intelligent; it is actually closer to “filtered garbage”. So identifying the pattern of Iambic Pentameter, for example, is still an artificial process. It can be computed mathematically with a large enough data set. Scale those patterns to music, art, literature, and the more sophisticated patterns that make up our repertoire of human creativity and it is impressive – but still synthesized. Information processing is still very primitive, and lacks many of the traits of human understanding. The inability to conceive tradition, authority, and prejudice is why all of this advanced technology still leaves us with Nazi chatbots. Some would call this confirmation theory, which is an area quite underdeveloped (and the AI reading this wouldn’t disagree). Even the raw objectives of AI are based on human-engineered goals, and evaluated using performance metrics to select the best behavior. This is a very mechanical process. Certain behaviors we may view as creative tasks may in fact be simple randomness introduced into most AIs to avoid infinite logic loops. In short, a lot of what you see is quite the opposite of the autonomous, self-motivated behavior it looks like. Any good AI behaves rationally only because someone programmed good objectives into it. Garbage in, garbage out.
One of the big differences between traditional forms of ML and generative AI is the direction in which the data flows. Traditionally, inputs flow into the system for training and queries. To train traditional systems, you’d suck in “a bunch of other people’s stuff”, and it identifies all of the interesting patterns that are then compared with the input sample. Generative AI takes this a step further, and flips the switch on the vacuum cleaner – and now all of the dirt that was initially fed into the system is shot out the pipe to produce the equivalent of a digital dust cloud of the original training medium. The output of generative AI takes the critical patterns and concepts weighted during the AI’s training and applies some formative computation to produce its own reference sample as a result. Neat-o. Nice parlor trick.
With billions of dollars, this ML scales to perform impressive computational tasks. The risk of this type of system goes beyond the traditional vision of a robot building a better chair, or replacing a worker at a plant. Today’s ML systems are white collar professionals and don’t require mechanical bodies; the computational capabilities of these systems can replace a broad array of professions using the thought product of millions of humans at once – so how could anyone compete with that? No one was ever supposed to, in fact. Doug Englebart, pioneer in the field of human-computer interaction, saw AI’s value more in intelligence-augmentation (that is, IA rather than AI), as a means of assisting the worker. Corporate greed has already led to the recent misapplication of AI, using its advanced capabilities to replace, rather than to augment, humans. Hollywood’s ML generation of “extras” is a quite extreme and literal example of this. But corporate greed isn’t AI generated. AI is replacing employees for very human reasons, and little to do with artificial intelligence itself. Yet correct computer-human interfaces are a fundamental principle that many computer scientists and science fiction authors alike both fear will be broken. Should you hate AI? No, you should hate greed.
The cold irony is this: at a deconstructed level, the output of generative AI represents the collective intelligence of other people’s thought products – their ideas, writings, music, theology, facts, opinions, and so on, likely also including those who lose their job to it. This also means others’ patents and copyrighted works, either directly or indirectly. ML has proven wildly successful at identifying the most effective critical patterns and gluing them together in some coherent form that communicates a desired result – but at the end of the day, all of its intelligence indeed belongs to the other people whose content was used to train it, almost always without their permission. In the end, generative AI takes from the world’s best authors, artists, musicians, philosophers, and other thinkers – erasing their identities, and taking their credit in its output. Without the proper restraints, it will produce the master forgeries of our generation. Should we forget its limitations and begin to rely on it for information, AI will easily blur the lines between what we view as real facts and synthesized ones. Consider a recent instance of this, where an attorney got himself in hot water for citing case law that didn’t exist – AI had seemingly fabricated it, where the attorney thought they were leveraging AI to do research. Imagine the impact to future case law should courtroom outcomes be based on unchecked fictional precedent! At some point in the future, there will be a demand for AI systems that fact check other AI systems, and then of course systems to fact check those systems. Disinformation and hallucinations will become harder to identify when a small sample is unintentionally used to train new AI systems.
Since When Don’t We Bless Gay People??!?
On February 23, 2023 by Jonathan Zdziarski
How can I curse those whom God has not cursed?
How can I denounce those whom the Lord has not denounced?
I have received a command to bless; he has blessed, and I cannot change it.
Numbers 23
Christians are expected to be a people who bless. We were commanded so, in fact. Luke 6:28 goes so far as to instruct Christians to “bless those who curse you, pray for those who mistreat you”; Romans 12:14 echoes this, “Bless those who persecute you; bless and do not curse”. The Christians closest to Jesus were instructed to bless in even the most extreme sense – those that would later torture and murder them for their very own Christian beliefs. How ironic then that bishops from the Global South Fellowship of Anglican Churches recently ousted the Archbishop of Centerbury for offering blessings to gay couples. A harmless gay couple looking to participate in the church hardly sounds like a threat to the faith – yet scripture would still insist we bless them even if they were. Anyone looking to be part of the church should in fact be welcomed with open arms. This matter is not one of a liberal or conservative posture. This is a matter of basic Christian love and grace – actually acting like a Christian.
While there’s a lot of room in the Anglican community for differences of opinion, it is within the very fabric of a Christian to be a people who bless. Christians are called to love as Jesus has loved us (John 15:12). Blessing others is one of the ways in which a Christian mimics Jesus; “If you love those who love you, what credit is that to you? If you do good to those that do good to you, what credit is that to you?” Refusing to bless others who don’t meet your bar of acceptability is not only inconsistent with the Jesus of scripture, it is exactly the kind of behavior Jesus railed against in the religious leaders of his day.
The church has taken the common practice of blessing others and wrapped it into more formal liturgy, which is fine. Building fences around these man-made constructs, however, is playing with fire, at best, and at the end of the day any theology that inhibits doing one of the most basic things that defines a Christian is just poor theology. In my opinion, such disobedience to the Christian ethos has no place in the church. What troubles me is that not only should these bishops know this, it should have been written on their hearts. We are not the gatekeepers of blessing, we are the salt of the earth.
Since when did Christianity become such an entitled religion? What the world needs is more blessing. More peace. More of God’s outpouring. Not less. I am grateful that in all of my failings as a Christian, God has still had his hand of spiritual blessing on me. It is the infinite grace of God that transforms people’s hearts and lives, yet that grace seems to all be forgotten when you put on a funny hat. It is apropos that during this Lent season, we should be remembering the ashes from which we came, and just how wretched, miserable, poor, blind and naked we all are without God. It is only by his grace that any of us should receive any blessing at all. As another Anglican bishop recently wrote, “we can only fully embrace God’s love and mercy when we come to terms with how completely unworthy of it we are.” Perhaps these other bishops – and maybe the rest of us could use a reminder from Matthew 10:8: Freely you have received, freely give.
Elon Musk Cannot Fathom Free Speech
On December 17, 2022 by Jonathan Zdziarski
I’ve recently written about the problems with social media in provoking speech and conformity, as well as the cult phenomenon that social media companies capitalize on. Elon Musk’s recent purchase of Twitter seems an apropos time to address the direct suppression of free speech.
Among Musk’s poorly thought out misadventures, he recently and rightfully reinstated the Twitter accounts of several journalists who had been critical of him in the past, whom he had previously rage-banned without warning. What’s really appalling to me isn’t that he suspended them in the first place (which was deeply troubling), but rather the guise under which he reinstated them. Like many of his twit-decisions, Musk started with a Twitter poll, regarded as having roughly the same credibility as a Russian election. This was followed with a decree that “the people have spoken”, referring to the disenfranchised twelve year olds, Russian trolls, and bots that vote on Twitter. Musk uses this business strategy, which cost $44 billion in research, whenever he wants to make a public policy decision that doesn’t involve putting people out of work. This policy-related polling seems almost an attempt to make the Twitterverse feel empowered by the new CEO.
Yet while Musk might have his users believe that they are now participants in the free speech narrative, the very concept of free speech itself is at odds with – even downright hostile to the notion of crowd-sourced policy. The Bill of Rights was designed intentionally to “prevent a sheep and two wolves from voting on what’s for dinner”. It seems to elude Musk that the right of free speech exists at a level higher than himself; that, rather than handing it out by vote, he is a mere steward of it with the responsibility of defending it. The Twitterverse at large has not and should not be empowered to make decisions about what speech to permit, because doing so destroys free speech. Failing to understand the requirements of such a basic human right is a dangerous thing for someone dictating policy of any system that depends on it. Musk, rather, seems to lack either the capacity or the restraint to make responsible decisions about free speech, or how to distinguish free speech from misinformation (today’s “Fire!” in a crowded theatre). Musk’s inability to handle such a delicate instrument of civil society is truly terrifying given the sheer amount of unilateral power he now has over public discourse.
Twitter was already a sick animal when Musk took over not long ago; the idea of giving a popular vote on speech policy to all users is not just the adolescent prank it looks like, but stands to set a dangerous norm across all social media platforms unless users push back on such an offensive thing. A society that believes the people should be allowed to choose what speech is acceptable is a society that burns books and compels conformity. Musk is simply taking the first step by normalizing this type of behavior among the online community. Anyone who is a free speech advocate should be condemning, not participating in it. If Musk doesn’t start to apply his brain here rather than his ego, Twitter 2.0 could very easily resemble German Student Union 1.0. Empowering children over others was how things started to go wrong back then too.
I had struggled to propose a solution to this problem, at least as far as Twitter is concerned, and then awoke to the most appropriate and fitting news on the subject: Musk created another poll, in which Twitter users voted he resign his post as CEO. It seems he occasionally does poll before putting people out of a job.
Christianity . Essays . Opinion . Politics
On Abortion and False Piety
On November 16, 2022 by Jonathan Zdziarski
The priest shall bring her and have her stand before the Lord. Then he shall take some holy water in a clay jar and put some dust from the tabernacle floor into the water. After the priest has had the woman stand before the Lord, he shall loosen her hair and place in her hands the reminder-offering, the grain offering for jealousy, while he himself holds the bitter water that brings a curse. Then the priest shall put the woman under oath and say to her, “If no other man has had sexual relations with you and you have not gone astray and become impure while married to your husband, may this bitter water that brings a curse not harm you. But if you have gone astray while married to your husband and you have made yourself impure by having sexual relations with a man other than your husband”— here the priest is to put the woman under this curse—“may the Lord cause you to become a curse[d] among your people when he makes your womb miscarry and your abdomen swell. May this water that brings a curse enter your body so that your abdomen swells or your womb miscarries. Then the woman is to say, “Amen. So be it.”
Documented use of an Abortifacient, Numbers 5:16-22
In May 2022, white evangelical Christians woke up to some rather unexpected news. A draft opinion had somehow leaked out of the Supreme Court, suggesting that Roe v. Wade would soon be overturned. Shortly after, it was. I single out white evangelicals here because, according to a recent Pew Research study, they are twice as likely to want to see abortion outlawed than other Americans (including other Christians). It would be an error though to conclude this means white evangelicals are the most pro-life. No no no, this is not the case at all. White evangelicals are no more pro-life than other religious groups, Christian or otherwise – they are, however, the most autocratic. Yet those who would use the Bible to institute government sponsored morality seem to have forgotten where the bodies are buried: also in their Bible.
The concept of abortion is nothing new. The practice of inducing an abortion as punishment for unfaithful women was once conducted as part of priestly duties in pre-Christian Judaism. A woman suspected of adultery, yet maintaining her innocence would be partially stripped, treated as an animal (right down to the presentation of an animal’s meal offering), and made to drink a type of holy water concoction; it was believed an unfaithful woman would abort her lover’s fetus and die within up to three years were she guilty (Mishnah Sotah 3). Holy water has a long tradition of being used to cleanse and purify, and so the implication was that the illegitimate fetus was evil, and therefore must be purged from the woman. Behind the scenes, this seemed to have more to do with the financial aspects of marriage contracts and intimidation than it did holiness, and the practice was eventually ended prior to the destruction of the second temple. Today’s American evangelicals take the opposing viewpoint of their ancestors – namely, against all forms of abortion – yet still firmly hold onto the practice of controlling women in much the same way. Yet while many other Christians value life just as much as autocratic evangelicals, we differ greatly from them particularly on a solution to the number of unwanted pregnancies in the country. The earliest Christians opposed abortion by adopting others’ discarded and unwanted live babies – a Roman practice known as “infant exposure” would leave abandoned babies in the trash or otherwise discarded after birth, left to die or be raised as slaves and prostitutes by others. It was this practice that many early writers condemned as “the worst abomination of all” (Philo of Alexandria). They wrote about Roman abortion practices far less. Yet while early Christians put their faith into action by sacrificially taking in these babies to save them from such a fate, today’s evangelicals largely believe opposing abortion through politics and legislation is the only solution. Most others believe it is an ineffective and dangerous solution – perhaps just as dangerous as the ancient practice that once caused them (or at least was perceived to; the practice’s effectiveness was highly questionable among rabbis).
Forced morality is likewise nothing new either. In the book of Chronicles, King Josiah breaks down the altars of false gods, tears down carved images, and rids Judah and Jerusalem of the ungodliness of the time. When his priest finds the Book of the Law, Josiah tears his robe and imposes moral rule according to the laws of the book. The chronicler Ezra writes, “Josiah removed all the detestable idols from all the territory belonging to the Israelites, and he had all who were present in Israel serve the Lord their God. As long as he lived, they did not fail to follow the Lord, the God of their ancestors.” An often overlooked detail in this story is that in spite of a society living under (and clearly practicing!) moral law, God tells Josiah that he will take his life early so that he will not see the disaster God plans to bring about. A useful object lesson can be found here: perceived morality counts for little when it is compelled. At the center of today’s controversy is not really Christian doctrine at all (there is no Christian doctrine concerning abortion), or even morality, but rather the same desire for power; today, that translates to the church’s desire for socio-economic power.
Christianity . Essays . Opinion . Politics
Evangelical Christianity is Broken
On November 15, 2022 by Jonathan Zdziarski
In the beginning wickedness did not exist. Nor indeed does it exist even now in those who are holy, nor does it in any way belong to their nature.
Athanasius, Against the Heathen
I’ve devoted much of the past 30 years as an evangelical Christian “layperson” to Christian studies to try and become an educated one. Greek, theology, the patristics, and Christian history should be in the wheelhouse of every Christian, yet many never study their own religion, and merely live confined to the prison of their own prejudice. Most Christians can’t tell the difference between culture and doctrine, and often conflate the two. It is, therefore, of little surprise that what Christianity has become in America is more or less a product of a news cycle, and less about a gospel of a meek savior. Evangelical Christianity in America broke in 2020, though perhaps some would say it’s been broken longer.
Ever since, the church stopped being recognizable – even to many Christians – in her embrace of racism, hostility, and misinformation that many Christian believers proliferate. It often failed to resemble a church at all, but rather a counterfeit designed to resemble Christianity in name only, almost certainly alien to what was truly being worshipped. The year 2020 brought some of the worst out in the mainstream evangelical church – relatives, friends, and people I’ve grown up with – who were once a much-needed example of Christianity to me – have severely disappointed in how they’d conducted themselves, causing me to question if they ever truly understood their own faith.
The Art of Understanding
On July 4, 2022 by Jonathan Zdziarski
We cannot understand without wanting to understand, that is, without wanting to let something be said… Understanding does not occur when we try to intercept what someone wants to say to us by claiming we already know it.
Hans-Georg Gadamer
Users of social media are attracted to platforms supporting free speech and open communication. The business motivations of social media are too, but for a different reason. A social media company’s valuation is largely driven by user activity metrics, from which advertising and media value are derived. The free speech that users value often turns out to be provoked, induced through controversy or cult phenomenon. Platform disruptors help drive up user activity by provoking speech, which benefits the value of the platform. The more disruptors a platform has (and the more freedom they’re given), the more controversy and virality will exist to improve those metrics that drive valuation. Provoked speech isn’t really free. The consequences of a platform engendering controversy and virality can be seen in the obvious de-evolution of social norms online: civility is rare, cruelty is ever increasing, and understanding no longer has the currency it once had. Outrage pays.
Understanding is key to any civil society. In America, we usually don’t take the time to understand one another anymore, particularly online. Without fully appreciating someone’s perspective, we usually end up seeing others through our own universe of norms; through our “own lens” as one might say. But it is that person’s own culture, knowledge and norms that influence their prejudices, their beliefs, and their treatment of a subject. Their experiences – not ours – formed their views. The only correct way to understand someone then is through their lens, treating our own as an impairment begging for a corrective prescription.
One of the great modern philosophers Hans-Georg Gadamer saw the study of hermeneutics as a means of gaining understanding of “the other” through an effort to transpose a person’s experiences, prejudices, and culture in a way that it could be uniquely appreciated despite the narrowness of our own. Think of it as a translation problem. When the effort is successful, there is a broadening of horizons to better understand how “the other” formed their network of beliefs, free from our own prejudices and norms. The rather sterile and parochial word hermeneutics might remind you more of Sunday School than social media, or more the type of legal research often used to interpret historical law than explain the psychology of a news cycle. If you were to consult college texts, you’d walk away quite certain that hermeneutics has nothing to do with everyday life and is the thing of dry people doing even drier historical things. Yet the doldrum historical sciences that employ hermeneutics have been grasping at the same basic goal to understand, which we often lack in social media.
How to Write Meaningful Assault Weapons Legislation
On May 24, 2022 by Jonathan Zdziarski
I originally published this in 2012, after the Sandy Hook shooting, and dust it off every time there’s a random mass shooting in the news. This post has seen the top of my feed year after year, as politicians continue to offer nothing, failing the majority of Americans who want to see new laws passed on firearms, prioritize mental health care, and integrate police more closely with schools to protect children, rather than compete with Wal-Mart to protect merchandise. I am deeply saddened by the recent mass shootings in the news, but even more saddened at what ineffective, impotent leaders we continue to elect in this country year over year.
I’ve been a long time responsible gun owner, by the old definition of what that used to mean. Like a majority of them, I’ve wanted more controls on semi-automatic rifles – particularly, assault rifles, for a long time. There’s idiocy on both sides of this debate, and both have some questionable notions about them. The extreme left seems to have developed an irrational fear and hatred of all guns and the extreme right ignorantly believes the only solution to guns are more guns. Consider this more sensible perspective from someone who spent over a decade shooting and working on guns, held NRA certifications to supervise ranges and carry concealed weapons, and up until some years ago – when I sold the rights to it – produced the #1 ballistics computer in the App Store.
While often obscure to most, there is – today – a system in place to perform intensive checks of individuals looking to own firearms categorized as highly lethal; the problem is it isn’t being used to control most assault rifles. Introduced in the National Firearms Act legislation, this system was applied to machine guns, short barrel rifles, silencers, sawed off shotguns, and other types of firearms that individuals can still legally own today, but with more than the casual regulation of AR-15s and other firearms. It could be changed to include semi-automatic rifles with the stroke of a pen. In my opinion, it should be, and in this post I’ll argue why I’d like the President and legislators push for this.
Edward Snowden in Hindsight
On March 22, 2022 by Jonathan Zdziarski
I only regret that I have but one life to lose for my country.
Nathan Hale
On the day of Nathan Hale’s execution, a British officer wrote of Hale, “he behaved with great composure and resolution, saying he thought it the duty of every good Officer, to obey any orders given him by his Commander-in-Chief; and desired the Spectators to be at all times prepared to meet death in whatever shape it might appear.” Nearly ten years ago, I viewed Edward Snowden as a slightly nerdier, yet similar patriot to the greats. I wanted to believe he was serving his country, and was unfairly targeted by the state for standing up for those beliefs. Much of tech did too, which is why this is an important discussion to have. It’s affected how the tech community views and interacts with government in many ways, with all of the prejudices it brought into play. For all the pontificating since then about freedom that Snowden has done, his taking up permanent citizenship in Russia, and his silence since the beginning of the war with Ukraine (except, more recently, to criticize the US once more), today I rather see the pattern of a common deserter in Snowden, rather than the champion of free speech that some position him as. If Snowden is to set the narrative for how tech views and responds to government, then our occasional criticism of his own behavior should be fair game.
During his time in Russia, we have seen the whistleblower system work effectively here at home. The details of Trump’s Ukraine call, and the subsequent freezing of security aid seems rather relevant today. More impressively so, this same whistleblower system Snowden criticized worked against a sitting president having no capacity for restraint. The fruits of it were significant, and the process brought both public dissemination and a full press by congress to protect the whistleblower. Mr. X, whose identity is still somewhat contested, was a hero. He stood up to the bully, knowing better than most how lawless the tyrant was, and of the angry mob he commanded. What happened to X? Very little, certainly far less than the charges Snowden brought on himself or the freedoms he gave up by not using the right channels. Instead of following process, Snowden fled the country under the Obama administration, who was a teddy bear compared to Trump. Snowden rejected this government process, insisting the whistleblower system was corrupt, using it as justification to leak classified documents, shortly before departing the country. In 2020, he asked us to excuse him again while he applied for Russian citizenship “for the sake of his kids”. Yet even in being proved wrong by a true hero like X while the country lived under a tyrant, Snowden continues to hide from the consequences of this terrible miscalculation.