What is an “algorithm”? It depends whom you ask
Similarly, New York City is considering Int 1894, a law that would introduce mandatory audits of “automated employment decision tools,” defined as “any system whose function is governed by statistical theory, or systems whose parameters are defined by such systems.” Notably, both bills mandate audits but provide only high-level guidelines on what an audit is.
As decision-makers in both government and industry create standards for algorithmic audits, disagreements about what counts as an algorithm are likely. Rather than trying to agree on a common definition of “algorithm” or a particular universal auditing technique, we suggest evaluating automated systems primarily based on their impact. By focusing on outcome rather than input, we avoid needless debates over technical complexity. What matters is the potential for harm, regardless of whether we’re discussing an algebraic formula or a deep neural network.
Impact is a critical assessment factor in other fields. It’s built into the classic DREAD framework in cybersecurity, which was first popularized by Microsoft in the early 2000s and is still used at some corporations. The “A” in DREAD asks threat assessors to quantify “affected users” by asking how many people would suffer the impact of an identified vulnerability. Impact assessments are also common in human rights and sustainability analyses, and we’ve seen some early developers of AI impact assessments create similar rubrics. For example, Canada’s Algorithmic Impact Assessment provides a score based on qualitative questions such as “Are clients in this line of business particularly vulnerable? (yes or no).”
There are certainly difficulties to introducing a loosely defined term such as “impact” into any assessment. The DREAD framework was later supplemented or replaced by STRIDE, in part because of challenges with reconciling different beliefs about what threat modeling entails. Microsoft stopped using DREAD in 2008.
In the AI field, conferences and journals have already introduced impact statements with varying degrees of success and controversy. It’s far from foolproof: impact assessments that are purely formulaic can easily be gamed, while an overly vague definition can lead to arbitrary or impossibly lengthy assessments.
Still, it’s an important step forward. The term “algorithm,” however defined, shouldn’t be a shield to absolve the humans who designed and deployed any system of responsibility for the consequences of its use. This is why the public is increasingly demanding algorithmic accountability—and the concept of impact offers a useful common ground for different groups working to meet that demand.
Kristian Lum is an assistant research professor in the Computer and Information Science Department at the University of Pennsylvania.
Rumman Chowdhury is the director of the Machine Ethics, Transparency, and Accountability (META) team at Twitter. She was previously the CEO and founder of Parity, an algorithmic audit platform, and global lead for responsible AI at Accenture.
Google just launched Bard, its answer to ChatGPT—and it wants you to make it better
Google has a lot riding on this launch. Microsoft partnered with OpenAI to make an aggressive play for Google’s top spot in search. Meanwhile, Google blundered straight out of the gate when it first tried to respond. In a teaser clip for Bard that the company put out in February, the chatbot was shown making a factual error. Google’s value fell by $100 billion overnight.
Google won’t share many details about how Bard works: large language models, the technology behind this wave of chatbots, have become valuable IP. But it will say that Bard is built on top of a new version of LaMDA, Google’s flagship large language model. Google says it will update Bard as the underlying tech improves. Like ChatGPT and GPT-4, Bard is fine-tuned using reinforcement learning from human feedback, a technique that trains a large language model to give more useful and less toxic responses.
Google has been working on Bard for a few months behind closed doors but says that it’s still an experiment. The company is now making the chatbot available for free to people in the US and the UK who sign up to a waitlist. These early users will help test and improve the technology. “We’ll get user feedback, and we will ramp it up over time based on that feedback,” says Google’s vice president of research, Zoubin Ghahramani. “We are mindful of all the things that can go wrong with large language models.”
But Margaret Mitchell, chief ethics scientist at AI startup Hugging Face and former co-lead of Google’s AI ethics team, is skeptical of this framing. Google has been working on LaMDA for years, she says, and she thinks pitching Bard as an experiment “is a PR trick that larger companies use to reach millions of customers while also removing themselves from accountability if anything goes wrong.”
Google wants users to think of Bard as a sidekick to Google Search, not a replacement. A button that sits below Bard’s chat widget says “Google It.” The idea is to nudge users to head to Google Search to check Bard’s answers or find out more. “It’s one of the things that help us offset limitations of the technology,” says Krawczyk.
“We really want to encourage people to actually explore other places, sort of confirm things if they’re not sure,” says Ghahramani.
This acknowledgement of Bard’s flaws has shaped the chatbot’s design in other ways, too. Users can interact with Bard only a handful of times in any given session. This is because the longer large language models engage in a single conversation, the more likely they are to go off the rails. Many of the weirder responses from Bing Chat that people have shared online emerged at the end of drawn-out exchanges, for example.
Google won’t confirm what the conversation limit will be for launch, but it will be set quite low for the initial release and adjusted depending on user feedback.
Google is also playing it safe in terms of content. Users will not be able to ask for sexually explicit, illegal, or harmful material (as judged by Google) or personal information. In my demo, Bard would not give me tips on how to make a Molotov cocktail. That’s standard for this generation of chatbot. But it would also not provide any medical information, such as how to spot signs of cancer. “Bard is not a doctor. It’s not going to give medical advice,” says Krawczyk.
Perhaps the biggest difference between Bard and ChatGPT is that Bard produces three versions of every response, which Google calls “drafts.” Users can click between them and pick the response they prefer, or mix and match between them. The aim is to remind people that Bard cannot generate perfect answers. “There’s the sense of authoritativeness when you only see one example,” says Krawczyk. “And we know there are limitations around factuality.”
How AI experts are using GPT-4
Hoffman got access to the system last summer and has since been writing up his thoughts on the different ways the AI model could be used in education, the arts, the justice system, journalism, and more. In the book, which includes copy-pasted extracts from his interactions with the system, he outlines his vision for the future of AI, uses GPT-4 as a writing assistant to get new ideas, and analyzes its answers.
A quick final word … GPT-4 is the cool new shiny toy of the moment for the AI community. There’s no denying it is a powerful assistive technology that can help us come up with ideas, condense text, explain concepts, and automate mundane tasks. That’s a welcome development, especially for white-collar knowledge workers.
However, it’s notable that OpenAI itself urges caution around use of the model and warns that it poses several safety risks, including infringing on privacy, fooling people into thinking it’s human, and generating harmful content. It also has the potential to be used for other risky behaviors we haven’t encountered yet. So by all means, get excited, but let’s not be blinded by the hype. At the moment, there is nothing stopping people from using these powerful new models to do harmful things, and nothing to hold them accountable if they do.
Chinese tech giant Baidu just released its answer to ChatGPT
So. Many. Chatbots. The latest player to enter the AI chatbot game is Chinese tech giant Baidu. Late last week, Baidu unveiled a new large language model called Ernie Bot, which can solve math questions, write marketing copy, answer questions about Chinese literature, and generate multimedia responses.
A Chinese alternative: Ernie Bot (the name stands for “Enhanced Representation from kNowledge IntEgration;” its Chinese name is 文心一言, or Wenxin Yiyan) performs particularly well on tasks specific to Chinese culture, like explaining a historical fact or writing a traditional poem. Read more from my colleague Zeyi Yang.
Even Deeper Learning
Language models may be able to “self-correct” biases—if you ask them to
Large language models are infamous for spewing toxic biases, thanks to the reams of awful human-produced content they get trained on. But if the models are large enough, they may be able to self-correct for some of these biases. Remarkably, all we might have to do is ask.
Texas is trying out new tactics to restrict access to abortion pills online
Texas is trying to limit access to abortion pills by cracking down on internet service providers and credit card processing companies. These tactics reflect the reality that, post-Roe, the internet is a critical channel for people seeking information about abortion or trying to buy pills to terminate a pregnancy—especially in states where they can no longer access these things in physical pharmacies or medical centers.
Texas has long been a laboratory for anti-abortion political tactics, and on March 15, a US District Judge heard arguments in a case that’s seeking to reverse the FDA approval of mifepristone, a drug that can be used to terminate an early pregnancy. The case would limit online-facilitated abortions and would have far-reaching consequences even in states that are not trying to restrict abortion.
Earlier this month, Republicans in the Texas state legislature introduced two bills to restrict access to abortion pills. The first bill, HB 2690, would require internet service providers (ISPs) to ban sites that provide access to the pills or information about obtaining them. Companies like AT&T and Spectrum would have to “make every reasonable and technologically feasible effort to block Internet access to information or material intended to assist or facilitate efforts to obtain an elective abortion or an abortion-inducing drug.” The bill would also forbid both publishers and ordinary people from providing information about access to abortion-inducing drugs.
The second bill, SB 1440, would make it a felony for credit card companies to process transactions for abortion pills, and would also make them liable to lawsuits from the public.
Blair Wallace, a policy and advocacy strategist at the ACLU of Texas, a nonprofit that advocates for civil liberties and reproductive choice, said the recent developments mark “a new frontier for the ways in which they’re coming for [abortion access],” adding: “It is really terrifying.”
Wallace sees it as a continuation of a strategy that seeks to criminalize whole abortion care networks with the aim of isolating people seeking abortions. More broadly, this strategy of censoring information and language has become a popular tactic in US culture wars in the last several years, and the proposed bill could incentivize platforms to aggressively remove information about abortion access out of concern for legal risk. Some sites, like Meta’s Instagram and Facebook, have reportedly removed information about abortion pills in the past.
So what might the outcome of all the Texas action be? Both the bill that targets ISPs and the mifepristone case this week are unprecedented, which means neither is likely to be successful. That said, the tactics are likely to stay. “Will we see it again next session? Will we see parts of this bill stripped down and put into amendments? There’s like a million ways that this can play out,” says Wallace. Anti-abortion political strategy is coordinated nationally even though the fights are playing out at a state level, and it’s likely that other states will target online spaces going forward.
Online abortion resources can pose risks to privacy. But there are lots of ways to access them more safely. Here are some resources I recommend.