What is ‘lived experience’?


Article by Patrick J Casey: “Everywhere you turn, there is talk of lived experience. But there is little consensus about what the phrase ‘lived experience’ means, where it came from, and whether it has any value. Although long used by academics, it has become ubiquitous, leaping out of the ivory tower and showing up in activism, government, consulting, as well as popular culture. The Lived Experience Leaders Movement explains that those who have lived experiences have ‘[d]irect, first-hand experience, past or present, of a social issue(s) and/or injustice(s)’. A recent brief from the US Department of Health and Human Services suggests that those who have lived experience have ‘valuable and unique expertise’ that should be consulted in policy work, since engaging those with ‘knowledge based on [their] perspective, personal identities, and history’ can ‘help break down power dynamics’ and advance equity. A search of Twitter reveals a constant stream of use, from assertions like ‘Your research doesn’t override my lived experience,’ to ‘I’m pretty sure you’re not allowed to question someone’s lived experience.’

A recurring theme is a connection between lived experience and identity. A recent nominee for the US Secretary of Labor, Julie Su, is lauded as someone who will ‘bring her lived experience as a daughter of immigrants, a woman of color, and an Asian American to the role’. The Human Rights Campaign asserts that ‘[l]aws and legislation must reflect the lived experiences of LGBTQ people’. An editorial in Nature Mental Health notes that incorporation of ‘people with lived experience’ has ‘taken on the status of a movement’ in the field.

Carried a step further, the notion of lived experience is bound up with what is often called identity politics, as when one claims to be speaking from the standpoint of an identity group – ‘in my lived experience as a…’ or, simply, ‘speaking as a…’ Here, lived experience is often invoked to establish authority and prompt deference from others since, purportedly, only members of a shared identity know what it’s like to have certain kinds of experience or to be a member of that group. Outsiders sense that they shouldn’t criticise what is said because, grounded in lived experience, ‘people’s spoken truths are, in and of themselves, truths.’ Criticism of lived experience might be taken to invalidate or dehumanise others or make them feel unsafe.

So, what is lived experience? Where did it come from? And what does it have to do with identity politics?…(More)”.

AI-Powered World Health Chatbot Is Flubbing Some Answers


Article by Jessica Nix: “The World Health Organization is wading into the world of AI to provide basic health information through a human-like avatar. But while the bot responds sympathetically to users’ facial expressions, it doesn’t always know what it’s talking about.

SARAH, short for Smart AI Resource Assistant for Health, is a virtual health worker that’s available to talk 24/7 in eight different languages to explain topics like mental health, tobacco use and healthy eating. It’s part of the WHO’s campaign to find technology that can both educate people and fill staffing gaps with the world facing a health-care worker shortage.

WHO warns on its website that this early prototype, introduced on April 2, provides responses that “may not always be accurate.” Some of SARAH’s AI training is years behind the latest data. And the bot occasionally provides bizarre answers, known as hallucinations in AI models, that can spread misinformation about public health.The WHO’s artificial intelligence tool provides public health information via a lifelike avatar.Source: Bloomberg

SARAH doesn’t have a diagnostic feature like WebMD or Google. In fact, the bot is programmed to not talk about anything outside of the WHO’s purview, including questions on specific drugs. So SARAH often sends people to a WHO website or says that users should “consult with your health-care provider.”

“It lacks depth,” Ramin Javan, a radiologist and researcher at George Washington University, said. “But I think it’s because they just don’t want to overstep their boundaries and this is just the first step.”..(More)”

We Need To Rewild The Internet


Article by Maria Farrell and Robin Berjon: “In the late 18th century, officials in Prussia and Saxony began to rearrange their complex, diverse forests into straight rows of single-species trees. Forests had been sources of food, grazing, shelter, medicine, bedding and more for the people who lived in and around them, but to the early modern state, they were simply a source of timber.

So-called “scientific forestry” was that century’s growth hacking. It made timber yields easier to count, predict and harvest, and meant owners no longer relied on skilled local foresters to manage forests. They were replaced with lower-skilled laborers following basic algorithmic instructions to keep the monocrop tidy, the understory bare.

Information and decision-making power now flowed straight to the top. Decades later when the first crop was felled, vast fortunes were made, tree by standardized tree. The clear-felled forests were replanted, with hopes of extending the boom. Readers of the American political anthropologist of anarchy and order, James C. Scott, know what happened next.

It was a disaster so bad that a new word, Waldsterben, or “forest death,” was minted to describe the result. All the same species and age, the trees were flattened in storms, ravaged by insects and disease — even the survivors were spindly and weak. Forests were now so tidy and bare, they were all but dead. The first magnificent bounty had not been the beginning of endless riches, but a one-off harvesting of millennia of soil wealth built up by biodiversity and symbiosis. Complexity was the goose that laid golden eggs, and she had been slaughtered…(More)”.

A Brief History of Automations That Were Actually People


Article by Brian Contreras: “If you’ve ever asked a chatbot a question and received nonsensical gibberish in reply, you already know that “artificial intelligence” isn’t always very intelligent.

And sometimes it isn’t all that artificial either. That’s one of the lessons from Amazon’s recent decision to dial back its much-ballyhooed “Just Walk Out” shopping technology, a seemingly science-fiction-esque software that actually functioned, in no small part, thanks to behind-the-scenes human labor.

This phenomenon is nicknamed “fauxtomation” because it “hides the human work and also falsely inflates the value of the ‘automated’ solution,” says Irina Raicu, director of the Internet Ethics program at Santa Clara University’s Markkula Center for Applied Ethics.

Take Just Walk Out: It promises a seamless retail experience in which customers at Amazon Fresh groceries or third-party stores can grab items from the shelf, get billed automatically and leave without ever needing to check out. But Amazon at one point had more than 1,000 workers in India who trained the Just Walk Out AI model—and manually reviewed some of its sales—according to an article published last year on the Information, a technology business website.

An anonymous source who’d worked on the Just Walk Out technology told the outlet that as many as 700 human reviews were needed for every 1,000 customer transactions. Amazon has disputed the Information’s characterization of its process. A company representative told Scientific American that while Amazon “can’t disclose numbers,” Just Walk Out has “far fewer” workers annotating shopping data than has been reported. In an April 17 blog post, Dilip Kumar, vice president of Amazon Web Services applications, wrote that “this is no different than any other AI system that places a high value on accuracy, where human reviewers are common.”…(More)”

The AI That Could Heal a Divided Internet


Article by Billy Perrigo: “In the 1990s and early 2000s, technologists made the world a grand promise: new communications technologies would strengthen democracy, undermine authoritarianism, and lead to a new era of human flourishing. But today, few people would agree that the internet has lived up to that lofty goal. 

Today, on social media platforms, content tends to be ranked by how much engagement it receives. Over the last two decades politics, the media, and culture have all been reshaped to meet a single, overriding incentive: posts that provoke an emotional response often rise to the top.

Efforts to improve the health of online spaces have long focused on content moderation, the practice of detecting and removing bad content. Tech companies hired workers and built AI to identify hate speech, incitement to violence, and harassment. That worked imperfectly, but it stopped the worst toxicity from flooding our feeds. 

There was one problem: while these AIs helped remove the bad, they didn’t elevate the good. “Do you see an internet that is working, where we are having conversations that are healthy or productive?” asks Yasmin Green, the CEO of Google’s Jigsaw unit, which was founded in 2010 with a remit to address threats to open societies. “No. You see an internet that is driving us further and further apart.”

What if there were another way? 

Jigsaw believes it has found one. On Monday, the Google subsidiary revealed a new set of AI tools, or classifiers, that can score posts based on the likelihood that they contain good content: Is a post nuanced? Does it contain evidence-based reasoning? Does it share a personal story, or foster human compassion? By returning a numerical score (from 0 to 1) representing the likelihood of a post containing each of those virtues and others, these new AI tools could allow the designers of online spaces to rank posts in a new way. Instead of posts that receive the most likes or comments rising to the top, platforms could—in an effort to foster a better community—choose to put the most nuanced comments, or the most compassionate ones, first…(More)”.

The CFPB wants to rein in data brokers


Article by Gaby Del Valle: “The Consumer Financial Protection Bureau wants to propose new regulations that would require data brokers to comply with the Fair Credit Reporting Act. In a speech at the White House earlier this month, CFPB Director Rohit Chopra said the agency is looking into policies to “ensure greater accountability” for companies that buy and sell consumer data, in keeping with an executive order President Joe Biden issued in late February.

Chopra said the agency is considering proposals that would define data brokers that sell certain types of data as “consumer reporting agencies,” thereby requiring those companies to comply with the Fair Credit Reporting Act (FCRA). The statute bans sharing certain kinds of data (e.g., your credit report) with entities unless they serve a specific purpose outlined in the law (e.g., if the report is used for employment purposes or to extend a line of credit to someone).

The CFBP views the buying and selling of consumer data as a national security issue, not just a matter of privacy. Chopra mentioned three massive data breaches — the 2015 Anthem leak, the 2017 Equifax hack, and the 2018 Marriott breach — as examples of foreign adversaries illicitly obtaining Americans’ personal data. “When Americans’ health information, financial information, and even their travel whereabouts can be assembled into detailed dossiers, it’s no surprise that this raises risks when it comes to safety and security,” Chopra said. But the focus on high-profile hacks obscures a more pervasive, totally legal phenomenon: data brokers’ ability to sell detailed personal information to anyone who’s willing to pay for it…(More)”.

Measuring the mobile body


Article by Laura Jung: “…While nation states have been collecting data on citizens for the purposes of taxation and military recruitment for centuries, its indexing, organization in databases and classification for particular governmental purposes – such as controlling the mobility of ‘undesirable’ populations – is a nineteenth-century invention. The French historian and philosopher Michel Foucault describes how, in the context of growing urbanization and industrialization, states became increasingly preoccupied with the question of ‘circulation’. Persons and goods, as well as pathogens, circulated further than they had in the early modern period. While states didn’t seek to suppress or control these movements entirely, they sought means to increase what was seen as ‘positive’ circulation and minimize ‘negative’ circulation. They deployed the novel tools of a positivist social science for this purpose: statistical approaches were used in the field of demography to track and regulate phenomena such as births, accidents, illness and deaths. The emerging managerial nation state addressed the problem of circulation by developing a very particular toolkit amassing detailed information about the population and developing standardized methods of storage and analysis.

One particularly vexing problem was the circulation of known criminals. In the nineteenth century, it was widely believed that if a person offended once, they would offend again. However, the systems available for criminal identification were woefully inadequate to the task.

As criminologist Simon Cole explains, identifying an unknown person requires a ‘truly unique body mark’. Yet before the advent of modern systems of identification, there were only two ways to do this: branding or personal recognition. While branding had been widely used in Europe and North America on convicts, prisoners and enslaved people, evolving ideas around criminality and punishment largely led to the abolition of physical marking in the early nineteenth century. The criminal record was established in its place: a written document cataloguing the convict’s name and a written description of their person, including identifying marks and scars…(More)”.

How Belgium is Giving Citizens a Say on AI


Article by Graham Wetherall-Grujić: “A few weeks before the European Parliament’s final debate on the AI Act, 60 randomly selected members of the Belgian public convened in Brussels for a discussion of their own. The aim was not to debate a particular piece of legislation, but to help shape a European vision on the future of AI, drawing on the views, concerns, and ideas of the public. 

They were taking part in a citizens’ assembly on AI, held as part of Belgium’s presidency of the European Council. When Belgium assumed the presidency for six months beginning in January 2024, they announced they would be placing “special focus” on citizens’ participation. The citizen panel on AI is the largest of the scheduled participation projects. Over a total of three weekends, participants are deliberating on a range of topics including the impact of AI on work, education, and democracy. 

The assembly comes at a point in time with rising calls for more public inputs on the topic of AI. Some big tech firms have begun to respond with participation projects of their own. But this is the first time an EU institution has launched a consultation on the topic. The organisers hope it will pave the way for more to come…(More)”.

The tech industry can’t agree on what open-source AI means. That’s a problem.


Article by Edd Gent: “Suddenly, “open source” is the latest buzzword in AI circles. Meta has pledged to create open-source artificial general intelligence. And Elon Musk is suing OpenAI over its lack of open-source AI models.

Meanwhile, a growing number of tech leaders and companies are setting themselves up as open-source champions. 

But there’s a fundamental problem—no one can agree on what “open-source AI” means. 

On the face of it, open-source AI promises a future where anyone can take part in the technology’s development. That could accelerate innovation, boost transparency, and give users greater control over systems that could soon reshape many aspects of our lives. But what even is it? What makes an AI model open source, and what disqualifies it?

The answers could have significant ramifications for the future of the technology. Until the tech industry has settled on a definition, powerful companies can easily bend the concept to suit their own needs, and it could become a tool to entrench the dominance of today’s leading players.

Entering this fray is the Open Source Initiative (OSI), the self-appointed arbiters of what it means to be open source. Founded in 1998, the nonprofit is the custodian of the Open Source Definition, a widely accepted set of rules that determine whether a piece of software can be considered open source. 

Now, the organization has assembled a 70-strong group of researchers, lawyers, policymakers, activists, and representatives from big tech companies like Meta, Google, and Amazon to come up with a working definition of open-source AI…(More)”.

New Jersey is turning to AI to improve the job search process


Article by Beth Simone Noveck: “Americans are experiencing some conflicting feelings about AI.

While people are flocking to new roles like prompt engineer and AI ethicist, the technology is also predicted to put many jobs at risk, including computer programmers, data scientists, graphic designers, writers, lawyers.

Little wonder, then, that a national survey by the Heldrich Center for Workforce Development found an overwhelming majority of Americans (66%) believe that they “will need more technological skills to achieve their career goals.” One thing is certain: Workers will need to train for change. And in a world of misinformation-filled social media platforms, it is increasingly important for trusted public institutions to provide reliable, data-driven resources.

In New Jersey, we’ve tried doing just that by collaborating with workers, including many with disabilities, to design technology that will support better decision-making around training and career change. Investing in similar public AI-powered tools could help support better consumer choice across various domains. When a public entity designs, controls and implements AI, there is a far greater likelihood that this powerful technology will be used for good.

In New Jersey, the public can find reliable, independent, unbiased information about training and upskilling on the state’s new MyCareer website, which uses AI to make personalized recommendations about your career prospects, and the training you will need to be ready for a high-growth, in-demand job…(More)”.