Your Mileage May Vary is an advice column offering you a unique framework for thinking through your moral dilemmas. It’s based on value pluralism — the idea that each of us has multiple values that are equally valid but that often conflict with each other. To submit a question, fill out this anonymous form. Here’s this week’s question from a reader, condensed and edited for clarity:

The Jewish High Holidays are coming up, and that includes Yom Kippur. It’s a holiday that encourages people to reflect on their behavior and make amends. That’s all well and good, but I’m someone who struggles with scrupulosity — constantly worrying about my morality and if I’m doing The Most Possible Good.

In practice this is far more paralyzing than motivating. Fixating on the ethical implications of all possible decisions makes it harder to take any action, and I’ve lost hours scouring my memories of my past behavior for immorality like a football player watching footage of their games to analyze what they could do differently. Guilt simply isn’t serving me, but I worry that saying to hell with all that means I’ll stop striving to be a better person and become morally complacent.

I’ve observed Yom Kippur for decades, and don’t want to simply avoid the day. But the holiday is a moral scrupulosity trigger. How do you think I should approach this? I want to stop feeling guilty for letting guilt get in my own way.

Have you ever heard the story about what happened when God decided to give the Bible to flesh-and-blood human beings? According to the ancient rabbis, the angels hated the idea. They argued that humans were deeply flawed mortals who didn’t deserve such a holy scripture; only angels could be worthy of it, so it should stay up in heaven.

It fell to Moses to rebut the angels’ argument. He asked them: What do you angels need the Bible for? The Bible says not to murder, not to commit adultery, not to steal — do you have jealousy or other emotions that could lead you to do those things? The Bible says to honor your father and mother — but you don’t have parents, so how could you ever do that? And the Bible says to sanctify the Sabbath — but you never do any work, so how could you even honor the Sabbath by resting?

The angels saw that Moses was right. Angels are really great at one thing: being perfect. But perfect creatures are static. They don’t experience painful challenges, they don’t grow, and they don’t make choices that add beauty to the world. We humans do those things. God gives the Bible to humans not to make them into angels — but to make them better at being the unique thing they are: human animals, with feelings, flaws, and all, that can learn to use their capabilities in more beautiful ways.

I think there’s a lot of wisdom in this story. And I want you to notice how far it is from demanding that humans do “The Most Possible Good.” That language suggests a maximizing ethical theory like utilitarianism, which says that we have to do the action that produces the greatest good for the greatest number. In other words, we have to optimize.

Moral optimization may be possible for angels, but not for humans. We each hold multiple values, and sometimes those values are in tension with each other, forcing us to strike a balance as best we can. We’re not omniscient beings who can know with certainty how best to strike the balance.

What’s more, sometimes different kinds of moral good straight-up conflict with each other. Think of a woman who faces a trade-off: She wants to become a nun but also wants to become a mother. She can’t balance between those options — she has to choose. And what’s the better choice? We can’t say because the options are incommensurable. There’s no single yardstick by which to measure them so we can’t compare them to find out which is greater.

Given that this complexity is baked into the human condition, it’s impossible to be a perfect optimizing machine. And the more you try to force yourself to be that, the harder it’ll be for you to actually help others, because you’ll just be so burned out. As you’ve already discovered, the optimizing mindset is exhausting — you end up expending a lot of precious mental resources that you could be spending on something else. It can even lead to paralysis. And a lot of the time, there’s no knowably best decision.

So instead of trying to optimize everything, you can adopt a goal that’s humbler but more realistic: to live in line with your values as best you can.

I know that can feel scary. Optimizing makes being human feel less risky. It provides a sense of control, and therefore a sense of safety. The unspoken premise is that if you optimize, you’ll never have to ask yourself: How could I screw up that badly?

But there’s another way to feel safe. It’s about leaning into the fact that we are imperfect and vulnerable creatures and that even when we’re trying our hardest there will be some things that we do not do optimally.

Of course, we should still try to live in line with our values. But in those moments when we fall short, we shouldn’t berate ourselves, thinking, “I sinned!” In Hebrew, the word we typically translate as “to sin” (lachto) actually means “to miss the mark.” It’s the same word we’d use to describe someone with a bow and arrow who’s targeting the bullseye but misses it slightly. This is a useful image, because it reminds us just how normal it is to miss the mark. Just as the archer’s arrow is buffeted around by the wind, we’re buffeted around by all the physical and psychological conditions acting upon us — naturally we won’t always hit the bullseye! And when we do miss the mark, we deserve compassion.

I know what you’re thinking: What if adopting this mindset means you’ll become morally complacent and let yourself off the hook too easily? This is one of the most common objections to practicing self-compassion. But research shows it’s not well-founded. In fact, psychologists have found that more self-compassionate people are better able to acknowledge when they’ve made a mistake. They’re more likely to want to apologize and make amends to others when they mess up. And they try to do better the next time around. Why? Because, to them, mistakes don’t feel so psychologically damning. That allows them to take more — not less — responsibility for their actions.

Yom Kippur can feel terrifying when any mistake you’ve made over the past year seems damning. But according to the ancient rabbis, Yom Kippur is not meant to be a somber day — it’s one of the happiest days of the year! After all, it was on Yom Kippur that Moses descended from Mount Sinai carrying the second set of tablets inscribed with the Ten Commandments, ready to gift them to the people.

You probably know what happened to the first set of tablets: Moses shattered them after seeing the Israelites engaged in idol worship. What’s less known is that, according to one rabbinic story, God’s response to the shattering of those tablets was to actually congratulate Moses. Why did God think breaking them was the right move? And what was different about the second set?

While the first tablets had been fashioned by God and God alone, the second tablets were a human-divine collaboration: Moses carved the stone and God inscribed the words. And while the first tablets contained only the words of the Ten Commandments — a black-and-white, rule-based morality — the rabbis tell us that the second tablets contained within them all the stories and interpretations that Jewish sages would later develop.

In other words, God recognized that you can’t just give humans a list of moral rules and call it a day. Maybe that would work for angels, who live in a simplified, disembodied world, but our ethical life is just too messy and multifaceted to be captured by any single set of universally binding moral principles. Yet God chose people over angels anyway, inviting us into the collaboration and embracing our humanness rather than rejecting it.

So, to the rabbis, Yom Kippur was a happy day because they fully expected that God would accept and embrace messy humans.

Please, don’t try to be more zealous than God.

When you’re taking action, by all means, aim your arrows as true as you can — try to hit the bullseye, the place that captures as much of what you value as possible. But once you’ve released the arrow from your bow, let it be.

If it turns out that you missed the mark, that you acted suboptimally, I put it to you that that is okay. You are not an angel. You are not a perfect optimizing machine. You do not have access to a magical mathematical formula that can consider countless incommensurable variables and spit out the very best move with certainty. You are human and you do the best you can with what you’ve got.

The wisdom of these millennia-old stories is that that’s good enough for God. Let it be good enough for you, too.

Bonus: What I’m reading

When it comes to AI, as California goes, so goes the nation. The biggest state in the US by population is also the central hub of AI innovation for the entire globe, home to 32 of the world’s top 50 AI companies. That size and influence have given the Golden State the weight to become a regulatory trailblazer, setting the tone for the rest of the country on environmental, labor, and consumer protection regulations — and more recently, AI as well.

Now, following the dramatic defeat of a proposed federal moratorium on states regulating AI in July, California policymakers see a limited window of opportunity to set the stage for the rest of the country’s AI laws. In the early hours of Saturday morning, the California State Assembly voted in favor of SB 53, a bill that would require transparency reports from the developers of highly powerful, “frontier” AI models. The bill, which has passed both parts of the state legislature, now goes to Gov. Gavin Newsom to either be vetoed or signed into law.

The models targeted represent the cutting-edge of AI — extremely adept generative systems that require massive amounts of data and computing power, like OpenAI’s ChatGPT, Google’s Gemini, xAI’s Grok, and Anthropic’s Claude.

AI can offer tremendous benefits, but as the bill is meant to address, it’s not without risks. And while there is no shortage of existing risks from issues like job displacement and bias, SB 53 focuses on possible “catastrophic risks” from AI. Such risks include AI-enabled biological weapons attacks and rogue systems carrying out cyberattacks or other criminal activity that could conceivably bring down critical infrastructure. Such catastrophic risks represent widespread disasters that could plausibly threaten human civilization at local, national, and global levels. They represent risks of the kind of AI-driven disasters that have not yet occurred, rather than already-realized, more personal harms like AI deepfakes.

Exactly what constitutes a catastrophic risk is up for debate, but SB 53 defines it as a “foreseeable and material risk” of an event that causes more than 50 casualties or over $1 billion in damages that a frontier model plays a meaningful role in contributing to. How fault is determined in practice would be up to the courts to interpret. It’s hard to define catastrophic risk in law when the definition is far from settled, but doing so can help us protect against both near- and long-term consequences.

By itself, a single state bill focused on increased transparency will probably not be enough to prevent devastating cyberattacks and AI-enabled chemical, biological, radiological, and nuclear weapons. But the bill represents an effort to regulate this fast-moving technology before it outpaces our efforts at oversight.

SB 53 is the third state-level bill to try to specifically focus on regulating AI’s catastrophic risks, after California’s SB 1047, which passed the legislature only to be vetoed by the governor — and New York’s Responsible AI Safety and Education (RAISE) Act, which recently passed the New York legislature and is now awaiting Gov. Kathy Hochul’s approval.

SB 53, which was introduced by state Sen. Scott Wiener in February, requires frontier AI companies to develop safety frameworks that specifically detail how they approach catastrophic risk reduction. Before deploying their models, companies would have to publish safety and security reports. The bill also gives them 15 days to report “critical safety incidents” to the California Office of Emergency Services, and establishes whistleblower protections for employees who come forward about unsafe model deployment that contributes to catastrophic risk. SB 53 aims to hold companies publicly accountable for their AI safety commitments, with a financial penalty up to $1 million per violation.

In many ways, SB 53 is the spiritual successor to SB 1047, also introduced by Wiener.

Both cover large models that are trained at 10^26 FLOPS, a measurement of very significant computing power used in a variety of AI legislation as a threshold for significant risk, and both bills strengthen whistleblower protections. Where SB 53 departs from SB 1047 is its focus on transparency and prevention

While SB 1047 aimed to hold companies liable for catastrophic harms caused by their AI systems, SB 53 formalizes sharing safety frameworks, which many frontier AI companies, including Anthropic, already do voluntarily. It focuses squarely on the heavy-hitters, with its rules applying only to companies that generate $500 million or more in gross revenue.

“The science of how to make AI safe is rapidly evolving, and it’s currently difficult for policymakers to write prescriptive technical rules for how companies should manage safety,” said Thomas Woodside, the co-founder of Secure AI Project, an advocacy group that aims to reduce extreme risks from AI and is a sponsor of the bill, over email. “This light touch policy prevents backsliding on commitments and encourages a race to the top rather than a race to the bottom.”

Part of the logic of SB 53 is the ability to adapt the framework as AI progresses. The bill authorizes the California Attorney General to change the definition of a large developer after January 1, 2027, in response to AI advances.

Proponents of the bill were optimistic about its chances of being signed by the governor should it pass the legislature. On the same day that Gov. Newsom vetoed SB 1047, he commissioned a working group focusing solely on frontier models. The resulting report by the group provided the foundation for SB 53. “I would guess, with roughly 75 percent confidence, that SB 53 will be signed into law by the end of September,” said Dean Ball — former White House AI policy adviser, vocal SB 1047 critic, and SB 53 supporter — to Transformer.

But several industry organizations rallied in opposition, arguing that additional compliance regulation would be expensive, given that AI companies should already be incentivized to avoid catastrophic harms. OpenAI has lobbied against it, and technology trade group Chamber of Progress argues that the bill would require companies to file unnecessary paperwork and unnecessarily stifle innovation.

“Those compliance costs are merely the beginning,” Neil Chilson, head of AI policy at the Abundance Institute, told me over email. “The bill, if passed, would feed California regulators truckloads of company information that they will use to design a compliance industrial complex.”

By contrast, Anthropic enthusiastically endorsed the bill on Monday. “The question isn’t whether we need AI governance – it’s whether we develop it thoughtfully today or reactively tomorrow,” the company explained in a blog post. “SB 53 offers a solid path toward the former.” (Disclosure: Vox Media is one of several publishers that have signed partnership agreements with OpenAI, while Future Perfect is funded in part by the BEMC Foundation, whose major funder was also an early investor in Anthropic. Neither organization has editorial input into our content.)

The debate over SB 53 ties into broader disagreements about whether states or the federal government should drive AI safety regulation. But since the vast majority of these companies are based in California, and nearly all do business there, the state’s legislation matters for the entire country.

“A federally led transparency approach is far, far, far preferable to the multi-state alternative,” where a patchwork of state regulations can conflict with each other, said Cato Institute technology policy fellow Matthew Mittelsteadt in an email. But “I love that the bill has a provision that would allow companies to defer to a future alternative federal standard.”

“The natural question is whether a federal approach can even happen,” Mittelsteadt continued. “In my opinion, the jury is out on that but the possibility is far more likely that some suggest. It’s been less than 3 years since ChatGPT was released. That is hardly a lifetime in public policy.”

But in a time of federal gridlock, frontier AI advancements won’t wait for Washington.

The catastrophic risk divide

The bill’s focus on, and framing of, catastrophic risks is not without controversy.

The idea of catastrophic risk comes from the fields of philosophy and quantitative risk assessment. Catastrophic risks are downstream of existential risks, which threaten humanity’s actual survival or else permanently reduce our potential as a species. The hope is that if these doomsday scenarios are identified and prepared for, they can be prevented or at least mitigated.

But if existential risks are clear — the end of the world, or at least as we know it — what falls under the catastrophic risk umbrella, and the best way to prioritize those risks, depends on who you ask. There are longtermists, people focused primarily on humanity’s far future, who place a premium on things like multiplanetary expansion for human survival. They’re often chiefly concerned by risks from rogue AI or extremely lethal pandemics. Neartermists are more preoccupied with existing risks, like climate change, mosquito vector-borne disease, or algorithmic bias. These camps can blend into one another — neartermists would also like to avoid getting hit by asteroids that could wipe out a city, and longtermists don’t dismiss risks like climate change — and the best way to think of them is like two ends of a spectrum rather than a strict binary.

You can think of the AI ethics and AI safety frameworks as the near- and longtermism of AI risk, respectively. AI ethics is about the moral implications of the ways the technology is deployed, including things like algorithmic bias and human rights, in the present. AI safety focuses on catastrophic risks and potential existential threats. But, as Vox’s Julia Longoria reported in the Good Robot series for Unexplainable, there are inter-personal conflicts leading these two factions to work against each other, much of which has to do with emphasis. (AI ethics people argue that catastrophic risk concerns over-hype AI capabilities and ignores its impact on vulnerable people right now, while AI safety people worry that if we focus too much on the present, we won’t have ways to mitigate larger-scale problems down the line.)

But behind the question of near versus long-term risks lies another one: what, exactly, constitutes a catastrophic risk?

SB 53 initially set the standard for catastrophic risk at 100 rather than 50 casualties — similar to New York’s RAISE Act — before halving the threshold in an amendment to the bill. While the average person might consider, say, many people driven to suicide after interacting with AI chatbots to be catastrophic, such a risk is outside of the bill’s scope. (The California State Assembly just passed a separate bill to regulate AI companion chatbots by preventing them from participating in discussions about suicidal ideation or sexually explicit material.)

SB 53 focuses squarely on harms from “expert-level” frontier AI model assistance in developing or deploying chemical, biological, radiological, and nuclear weapons; committing crimes like cyberattacks or fraud; and “loss of control” scenarios where AIs go rogue, behaving deceptively to avoid being shut down and replicating themselves without human oversight. For example, an AI model could be used to guide the creation of a new deadly virus that infects millions and kneecaps the global economy.

“The 50 to 100 deaths or a billion dollars in property damage is just a proxy to capture really widespread and substantial impact,” said Scott Singer, lead author of the California Report for Frontier AI Policy, which helped inform the basis of the bill. “We do look at like AI-enabled or AI potentially [caused] or correlated suicide. I think that’s like a very serious set of issues that demands policymaker attention, but I don’t think it’s the core of what this bill is trying to address.”

Transparency is helpful in preventing such catastrophes because it can help raise the alarm before things get out of hand, allowing AI developers to correct course. And in the event that such efforts fail to prevent a mass casualty incident, enhanced safety transparency can help law enforcement and the courts figure out what went wrong. The challenge there is that it can be difficult to determine how much a model is accountable for a specific outcome, Irene Solaiman, the chief policy officer at Hugging Face, a collaboration platform for AI developers, told me over email.

“These risks are coming and we should be ready for them and have transparency into what the companies are doing,” said Adam Billen, the vice president of public policy at Encode, an organization that advocates for responsible AI leadership and safety. (Encode is another sponsor of SB 53.) “But we don’t know exactly what we’re going to need to do once the risks themselves appear. But right now, when those things aren’t happening at a large scale, it makes sense to be sort of focused on transparency.”

However, a transparency-focused bill like SB 53 is insufficient for addressing already-existing harms. When we already know something is a problem, the focus should be on mitigating it.

“Maybe four years ago, if we had passed some sort of transparency legislation like SB 53 but focused on those harms, we might have had some warning signs and been able to intervene before the widespread harms to kids started happening,” Billen said. “We’re trying to kind of correct that mistake on these problems and get some sort of forward-facing information about what’s happening before things get crazy, basically.”

SB 53 risks being both overly narrow and unclearly scoped. We have not yet faced these catastrophic harms from frontier AI models, and the most devastating risks might take us entirely by surprise. We don’t know what we don’t know.

It’s also certainly possible that models trained below 10^26 FLOPS, which aren’t covered by SB 53, have the potential to cause catastrophic harm under the bill’s definition. The EU AI Act sets the threshold for “systemic risk” at the smaller 10^25 FLOPS, and there’s disagreement about the utility of computational power as a regulatory standard at all, especially as models become more efficient.

As it stands right now, SB 53 occupies a different niche from bills focused on regulating AI use in mental healthcare or data privacy, reflecting its authors’ desire not to step on the toes of other legislation or bite off more than it can reasonably chew. But Chilson, the Abundance Institute’s head of AI policy, is part of a camp that sees SB 53’s focus on catastrophic harm as a “distraction” from the real near-term benefits and concerns, like AI’s potential to accelerate the pace of scientific research or create nonconsensual deepfake imagery, respectively.

That said, deepfakes could certainly cause catastrophic harm. For instance, imagine a hyper-realistic deepfake impersonating a bank employee to commit fraud at a multibillion-dollar scale, said Nathan Calvin, the vice president of state affairs and general counsel at Encode. “I do think some of the lines between these things in practice can be a bit blurry, and I think in some ways…that is not necessarily a bad thing,” he told me.

It could be that the ideological debate around what qualifies as catastrophic risks, and whether that’s worthy of our legislative attention, is just noise. The bill is intended to regulate AI before the proverbial horse is out of the barn. The average person isn’t going to worry about the likelihood of AI sparking nuclear warfare or biological weapons attacks, but they do think about how algorithmic bias might affect their lives in the present. But in trying to prevent the worst-case scenarios, perhaps we can also avoid the “smaller,” nearer harms. If they’re effective, forward-facing safety provisions designed to prevent mass casualty events will also make AI safer for individuals.

If Gov. Newsom signs SB 53 into law, it could inspire other state attempts at AI regulation through a similar framework, and eventually encourage federal AI safety legislation to move forward.

How we think about risk matters because it determines where we focus our efforts on prevention. I’m a firm believer in the value of defining your terms, in law and debate. If we’re not on the same page about what we mean when we talk about risk, we can’t have a real conversation.

Update, September 13, 2025, 11:55 am ET: This story was originally published on September 12 and has been updated to reflect the outcome of the California State Assembly vote.