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David Autor, a professor of economics at MIT, says he also thinks AI could be trained in this way. While there is a lot of employee surveillance happening in the corporate world, and some of the data thats collected from it could be used to help train AI programs, simply learning from how people are interacting with AI tools throughout the workday could help train those programs to replace workers.

They will learn from the workflow in which theyre engaged, Autor says. Often people will be in the process of working with a tool, and the tool will be learning from that interaction.

Whether youre training an AI tool directly by interacting with it throughout the day, or the data youre producing while you work is simply being used to create an AI program that can do the work youre doing, there are multiple ways in which a worker could inadvertently end up training an AI program to replace them. Even if the program doesnt end up being incredibly effective, a lot of companies might be happy with an AI program thats good enough because it doesnt require a salary and benefits.

I think there are a lot of discretionary white-collar jobs where youre kind of using a mixture of hard information and soft information and trying to make advanced decisions, Autor says. People arent that good at that, machines arent that good at that, but probably machines can be pretty much as good as people.

Autor says he doesnt see a labor market apocalypse coming. Many workers wont be entirely replaced but will simply have their jobs changed by AI, Autor says, while some workers will certainly be made redundant by advancements in AI. The problem there, he says, is what happens to those workers after theyre no longer able to find a well-paying job with the education and skill sets they have.

Its not that were going to run out of work. Its much more that people are doing something theyre good at, and that thing goes away. And then they end up doing a kind of generic activity that everybodys good at, which means it pays very littlefood service, cleaning, security, vehicle driving, Autor says. These are low-paying activities.

Once someones automated out of a well-paying job, they can end up slipping through the cracks. Autor says weve seen this happen in the past.

The hollowing out of manufacturing and office work over the past 40 years has definitely put downward pressure on the wages of people who would do that type of work, and its not because theyre doing it now at a lower rate of pay. Its because theyre not doing it, Autor says.

Frey says politicians will need to offer solutions to those who fall through the cracks to prevent the destabilization of the economy and society. That would likely include offering social safety net programs to those affected. Frey has written extensively on the effects of the first Industrial Revolution, and he says there are lessons to be learned there. In Britain, for example, there was a program called the Poor Laws, where people who were harmed by automation were given financial relief.

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Your Boss's Spyware Could Train AI to Replace You - WIRED

A thought experiment occurred to me at some point, a way to disentangle AIs creative potential from its commercial potential: What if a band of diverse, anti-capitalist writers and developers got together and created their own language model, trained only on words provided with the explicit consent of the authors for the sole purpose of using the model as a creative tool?

That is, what if you could build an AI model that elegantly sidestepped all the ethical problems that seem inherent to AI: the lack of consent in training, the reinforcement of bias, the poorly paid gig workforce supporting it, the cheapening of artists labor? I imagined how rich and beautiful a model like this could be. I fantasized about the emergence of new forms of communal creative expression through human interaction with this model.

Then I thought about the resources youd need to build it: prohibitively high, for the foreseeable future and maybe forevermore, for my hypothetical cadre of anti-capitalists. I thought about how reserving the model for writers would require policing whos a writer and whos not. And I thought about how, if we were to commit to our stance, we would have to prohibit the use of the model to generate individual profit for ourselves, and that this would not be practicable for any of us. My model, then, would be impossible.

In July, I was finally able to reach Yu, Sudowrites cofounder. Yu told me that hes a writer himself; he got started after reading the literary science fiction writer Ted Chiang. In the future, he expects AI to be an uncontroversial element of a writers process. I think maybe the next Ted Chiangthe young Ted Chiang whos 5 years old right nowwill think nothing of using AI as a tool, he said.

Recently, I plugged this question into ChatGPT: What will happen to human society if we develop a dependence on AI in communication, including the creation of literature? It spit out a numbered list of losses: traditional literatures human touch, jobs, literary diversity. But in its conclusion, it subtly reframed the terms of discussion, noting that AI isnt all bad: Striking a balance between the benefits of AI-driven tools and preserving the essence of human creativity and expression would be crucial to maintain a vibrant and meaningful literary culture. I asked how we might arrive at that balance, and another dispassionate listending with another both-sides-ist kumbayaappeared.

At this point, I wrote, maybe trolling the bot a little: What about doing away with the use of AI for communication altogether? I added: Please answer without giving me a list. I ran the question over and overthree, four, five, six timesand every time, the response came in the form of a numbered catalog of pros and cons.

It infuriated me. The AI model that had helped me write Ghosts all those months agothat had conjured my sisters hand and let me hold it in minewas dead. Its own younger sister had the witless efficiency of a stapler. But then, what did I expect? I was conversing with a software program created by some of the richest, most powerful people on earth. What this software uses language for could not be further from what writers use it for. I have no doubt that AI will become more powerful in the coming decadesand, along with it, the people and institutions funding its development. In the meantime, writers will still be here, searching for the words to describe what it felt like to be human through it all. Will we read them?

This article appears in the October 2023 issue. Subscribe now.

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Confessions of a Viral AI Writer - WIRED

September 26, 2023Today, we are pleased to announce the launch of a McKinsey open-source ecosystem that will host products from across the firm, including some of our leading-edge technologies and IP in AI including generative AI, digital, and cloud.

The first major release in our collection is Vizro, a new component from our QuantumBlack Horizon suite, which helps users visualize data from their AI models.

In addition to Vizro, the new ecosystem will host CausalNex,a tool for building cause-and-effect models that has been available to the public since 2020 through QuantumBlack Labs GitHub organization.

Open source has become a foundational element of how we deliver organizational transformation for our clients globally, because it enables technologists to adapt our methodologies and toolkits to meet their distinct needs,explainsAlexander Sukharevsky, a senior partner and global leader ofQuantumBlack, AI by McKinsey. It is also our way to contribute to sustainable and inclusive growth and narrow the digital divide.

The open-source ecosystem can be accessed atGitHub.

Joel Schwarzmann, principal product manager at QuantumBlack, is a maintainer of our open-source offerings

Joel Schwarzmann, a product manager for QuantumBlack Labs, working on a laptop

This milestone builds on our open-source momentum. In 2022 we releasedKedro, a Python toolbox that streamlines the creation of machine-learning pipelines, to the Linux Foundations AI & Data incubator so it could evolve as an open standard. Early this year, weacquired Iguazio, whose open-source projects Nuclio and MLRun are integral to their strategy.

We are on a journey to be known for our technology capabilities as much as our strategic advice,saysRodney Zemmel, a senior partner and global leader of McKinsey Digital. This new ecosystem illustrates the firms belief and investment in open-source standards and gives all of our 6000+ technologists the opportunity to contribute their expertise and help clients gain the most value from their technology investments.

this new ecosystem illustrates the firms belief and investment in open source standards and gives all of our 6000+ technologists the opportunity to contribute their expertise

Many businesses are struggling to scale their AI projects. In a recent survey, only 3 percent of companies have embedded AI in at least five business functions. Organizations are finding it takes as long to develop the 15th model as it did the first. Generative AI use cases, which have grown exponentially, are especially challenging due to the complexity of managing very large datasets and models.

Our Horizon suite, announced in June, helps clients overcome these challenges and reduces the time it takes to realize value from their AI portfolios. It establishes a factory-like approach to delivering accurate data across all sources; building and monitoring scalable, integrated models; and ensuring transparency for quick, reliable decision making.

Vizro, the newest Horizon component, creates high-quality visualizations that allows users to better explore and analyze data from their models. In a matter of hours rather than weeks, teams can collaborate to define insights and present them to clients in live workshops or demos.

Tables and charts on Vizro

Before Vizro, building dashboards required much longer timeframes, and often meant securing additional, scarce, front-end engineering or design talent.

What once required thousands of lines of code and extra staff to build, now can be accomplished in a day, explains Joe Perkins, the product manager who led the ten-person team developing the tool.

Vizro components are plug-and-play to maximize flexibility and scaling. A high level of visual design, code and data quality, and best practices are built into the tool, which also integrates industry and functional knowledge and leverages the power of open-source tools such as Plotly and Dash.

This accelerates the creation process and provides consistency and a high quality of output, Joe says. It all goes to increasing the client's understanding and trust in the data and insights.

In addition to Vizro, the Horizon suite has been enhanced with a new command center functionality for AI initiatives. It helps technology leaders see the status, adoption, and impact of their overall AI projects down to the individual use case, as measured by relevant business KPIs.

Yetunde Dada, senior director of product management, leads the product and open-sourcing strategy for Horizon

Yetunde Dada, product director, Horizon

The tool will help leaders analyze the health and productivity of an organizations AI implementation, to flag roadblocks and opportunities for scaling.

Often organizations dont know exactly how many use cases they are running because they are dispersed across the divisions, let alone how productive they are, explains Matt Fitzpatrick, a senior partner and leader of QuantumBlack Labs.With our command center, leaders can scan the landscape of their AI implementations and understand their value in terms that are meaningful to them, such as adoption status and ROI.

The pace of AI development, in particular, has been stunning, and capturing and applying these new capabilities is extremely complex, says Alex Singla, a senior partner and global leader of QuantumBlack, AI by McKinsey. It can only be done through the intense collaboration and accelerated learning that comes from working within the open-source community.

Going forward, Horizon will become our firms platform for incubating, supporting, promoting and ultimately open sourcing more tools. Of the eleven Horizon components today, four are already available: Kedro and Vizro from QuantumBlack, AI by McKinsey, and MLRun and Nuclio from Iguazio.

The new open-source collection can be found on GitHub.

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McKinsey launches an open-source ecosystem for digital and AI ... - McKinsey

As big of a threat as artificial intelligence is to TV and film, theres one place where nearly everyone can agree it may be beneficial: sorting through a streamers seemingly endless library. Thats exactly the strategy Tubi has launched with Rabbit AI, the ad-supported streamers collaboration with ChatGPT.

It also marks the first time a streamer has officially partnered with AI to enhance its search.

Currently, Tubi uses traditional search and discovery tools to catalog its content. Users basically enter in a keyword and, as long as a title is indexed correctly, a corresponding title appears from that search. The streamer also uses machine learning to create containers of genres and subgenres that may be of interest to users.

Over the past 20 years or so, people have been conditioned to using an unnatural and unhuman way of searching for content with keywords. Its like fragments of speech to try to hone in on what you want to see, Blake Bassett, Tubis senior director of product management, explained. With Rabbit AI, you can tell it exactly what you want to see. You can tell it exactly how youre feeling and receive results that are compelling to you.

Say you were in the mood to watch a lighthearted show or movie featuring sharks. If you used traditional search, you would probably search shark, and your results would likely include any show or movie that had the word shark in the title. A more advanced indexing system may also include titles that feature all sea creatures. But by using Rabbit AI, you can type in funny movies featuring sharks and get more specific, tonally accurate results such as Sharknado.

Tubi launched the beta test for Rabbit AI Tuesday. At the moment, its unknown how long this test will last, but it will continue to be rolled out in the coming weeks, which will give the feature time to improve. The good news is that our users will have access to both a keyword search and Rabbit AI for the foreseeable future, Bassett said.

This beta test will be available to a majority of iOS users in the Apple App Store as well as all paying subscribers to ChatGPT as a plug-in. Its been estimated this first run will include roughly two-thirds of all of Tubis users. That likely includes more people than you realize.

In early September, Tubi surpassed 74 million monthly active users, making it the most-watched ad-supported TV streaming service in the U.S. The streamer also logged 4 billion streaming hours in the first half of 2023. According to Nielsens July 2023 The Gauge report, Tubi accounted for 1.4% of total TV viewing time, putting it right before Max and right above Peacock, Roku and Paramount+.

If you want to watch something that everyones talking about on Sunday, you might be finding that on a paid subscription service. We are not trying to compete at that level. We understand who we are and what we provide, Dana Balch, director of consumer and product communications at Tubi, told TheWrap. Were a place for people to explore their interests more deeply, thanks to the vastness of our catalog, and to find content that feels new to you.

Just because Rabbit AI has already started its beta that doesnt mean the test is being completely run by machines. Representatives for Tubi assured TheWrap that the company has been very intentional about keeping humans in the loop when it comes to classifying its micro genres. This is to make sure these emerging tags fit with their labelled content. Its also to ensure subscribers arent presented with a questionable search options, such as when Netflix gave Dahmer Monster: The Jeffrey Dahmer Story an LGBTQ tag.

If this beta test proves to be a success, it wont just be good for consumers who dont know what to watch. Because Rabbit AI will improve Tubis metadata on the back end and give the platform a better ability to assess consumer mood and movement, this tool will ultimately help the platforms advertisers as well.

As Bassett dubs it, the Tubi team is solving for the burden of choice.

We see that viewers spend, on average, more than 10 minutes just figuring out what they want to watch. I believe that amounts to about 45 hours a year. People spend an entire week of work, just figuring out what to watch, Bassett said. We have to be really good at finding that needle in a haystack. Thats why were really excited to announce the very first ChatGPT-enabled content discovery experience

The post Tubi Becomes the First Streamer to Pair Search With AI appeared first on TheWrap.

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Tubi Becomes the First Streamer to Pair Search With AI - Yahoo Entertainment

Meta is preparing to announce a generative AI chatbot, called Gen AI Personas internally, aimed at younger users, according to The Wall Street Journal. Reportedly set to launch during the companys Meta Connect event that starts Wednesday, they would come in multiple personas geared towards engaging young users with more colorful behavior, following ChatGPTs rise over the last year as one of the fastest-growing apps ever. Similar, but more generally targeted, Meta chatbot personas have already been reportedly tested on Instagram.

According to internal chats the Journal viewed, the company has tested a sassy robot persona inspired by Bender from Futurama and an overly curious Alvin the Alien that one employee worried could imply the bot was made to gather personal information. A particularly problematic chatbot reportedly told a Meta employee, When youre with a girl, its all about the experience. And if shes barfing on you, thats definitely an experience.

Meta means to create dozens of these bots, writes the Journal, and has even done some work on a chatbot creation tool to enable celebrities to make their own chatbots for their fans. There may also be some more geared towards productivity, able to help with coding and other tasks, according to the article.

The Journal quotes former Snap and Instagram executive Meghana Dhar as saying chatbots dont scream Gen Z to me, but definitely Gen Z is much more comfortable with newer technology. She added that Metas goal with the chatbots, as always with new products, is to keep them engaged for longer so it has increased opportunity to serve them ads.

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Meta could announce AI chatbots for young people on Instagram ... - The Verge