Tools & Techniques.

https://www.cnbc.com/2023/07/07/three-ai-tools-to-make-you-more-efficient-at-work.html

CEO says these 3 A.I. tools can make you more efficient at work: They’re going to be ‘truly disruptive’

The internet is rife with conversations about the release of generative artificial intelligence tools like ChatGPT and what changes they could ultimately lead to in the job market. Worldwide, as many as 300 million jobs could be affected, according to a recent Goldman Sachs report. At the moment, however, a majority of business leaders plan to hire more as a result of their existence. Long term, experts agree no one knows what’s going to happen.

Meanwhile, early adopters of these AI tools are finding them to be a big help when it comes to day-to-day tasks.

Surveillance creep. (Good golly gosh, I wonder if the FBI knows about this?)

https://gizmodo.com/france-bill-allows-police-access-phones-camera-gps-1850609772

France Passes New Bill Allowing Police to Remotely Activate Cameras on Citizens' Phones

Amidst ongoing protests in France, the country has just passed a new bill that will allow police to remotely access suspects’ cameras, microphones, and GPS on cell phones and other devices.

As reported by Le Monde, the bill has been criticized by the French people as a “snoopers” charter that allows police unfettered access to the location of its citizens. Moreover, police can activate cameras and microphones to take video and audio recordings of suspects. The bill will reportedly only apply to suspects in crimes that are punishable by a minimum of five years in jail and Justice Minister Eric Dupond-Moretti claimed that the new provision would only affect a few dozen cases per year. During a debate over the bill yesterday, French politicians added an amendment that orders judge approval for any surveillance conducted under the scope of the bill and limits the duration of surveillance to six months, according to Le Monde.

Humor: Keep dreaming…

https://www.schneier.com/blog/archives/2023/07/the-ai-dividend.html

The AI Dividend

For four decades, Alaskans have opened their mailboxes to find checks waiting for them, their cut of the black gold beneath their feet. This is Alaska’s Permanent Fund, funded by the state’s oil revenues and paid to every Alaskan each year. We’re now in a different sort of resource rush, with companies peddling bits instead of oil: generative AI.

Everyone is talking about these new AI technologies—like ChatGPT—and AI companies are touting their awesome power. But they aren’t talking about how that power comes from all of us. Without all of our writings and photos that AI companies are using to train their models, they would have nothing to sell. Big Tech companies are currently taking the work of the American people, without our knowledge and consent, without licensing it, and are pocketing the proceeds.

You are owed profits for your data that powers today’s AI, and we have a way to make that happen. We call it the AI Dividend.

Our proposal is simple, and harkens back to the Alaskan plan. When Big Tech companies produce output from generative AI that was trained on public data, they would pay a tiny licensing fee, by the word or pixel or relevant unit of data. Those fees would go into the AI Dividend fund. Every few months, the Commerce Department would send out the entirety of the fund, split equally, to every resident nationwide. That’s it.

There’s no reason to complicate it further. Generative AI needs a wide variety of data, which means all of us are valuable—not just those of us who write professionally, or prolifically, or well. Figuring out who contributed to which words the AIs output would be both challenging and invasive, given that even the companies themselves don’t quite know how their models work. Paying the dividend to people in proportion to the words or images they create would just incentivize them to create endless drivel, or worse, use AI to create that drivel. The bottom line for Big Tech is that if their AI model was created using public data, they have to pay into the fund. If you’re an American, you get paid from the fund.

Under this plan, hobbyists and American small businesses would be exempt from fees. Only Big Tech companies—those with substantial revenue—would be required to pay into the fund. And they would pay at the point of generative AI output, such as from ChatGPT, Bing, Bard, or their embedded use in third-party services via Application Programming Interfaces.

Our proposal also includes a compulsory licensing plan. By agreeing to pay into this fund, AI companies will receive a license that allows them to use public data when training their AI. This won’t supersede normal copyright law, of course. If a model starts producing copyright material beyond fair use, that’s a separate issue.

Using today’s numbers, here’s what it would look like. The licensing fee could be small, starting at $0.001 per word generated by AI. A similar type of fee would be applied to other categories of generative AI outputs, such as images. That’s not a lot, but it adds up. Since most of Big Tech has started integrating generative AI into products, these fees would mean an annual dividend payment of a couple hundred dollars per person.

The idea of paying you for your data isn’t new, and some companies have tried to do it themselves for users who opted in. And the idea of the public being repaid for use of their resources goes back to well before Alaska’s oil fund. But generative AI is different: It uses data from all of us whether we like it or not, it’s ubiquitous, and it’s potentially immensely valuable. It would cost Big Tech companies a fortune to create a synthetic equivalent to our data from scratch, and synthetic data would almost certainly result in worse output. They can’t create good AI without us.

Our plan would apply to generative AI used in the US. It also only issues a dividend to Americans. Other countries can create their own versions, applying a similar fee to AI used within their borders. Just like an American company collects VAT for services sold in Europe, but not here, each country can independently manage their AI policy.

Don’t get us wrong; this isn’t an attempt to strangle this nascent technology. Generative AI has interesting, valuable, and possibly transformative uses, and this policy is aligned with that future. Even with the fees of the AI Dividend, generative AI will be cheap and will only get cheaper as technology improves. There are also risks—both every day and esoteric —posed by AI, and the government may need to develop policies to remedy any harms that arise.

Our plan can’t make sure there are no downsides to the development of AI, but it would ensure that all Americans will share in the upsides—particularly since this new technology isn’t possible without our contribution.

This essay was written with Barath Raghavan, and previously appeared on Politico.com.

Is this a license for journalistic surveillance?

https://www.pogowasright.org/law-against-secretly-recording-public-conversations-is-unconstitutional-ninth-circuit-rules/

Law Against Secretly Recording Public Conversations Is Unconstitutional, Ninth Circuit Rules

Avalon Zoppo reports:

The U.S. Court of Appeals for the Ninth Circuit on Monday struck down as unconstitutional an Oregon wiretapping law that bars secretly taping in-person conversations in public spaces, with a dissenting judge citing the rise of generative artificial intelligence “deepfakes” in support of a person’s right to have notice before being recorded.

The decision revives a lawsuit from Project Veritas, a conservative undercover media organization that claimed in a 2020 complaint that the law violated the First Amendment right to newsgathering. The group said the statute’s exceptions—one allowing the recording of life-endangering felonies and another of police officers—favors recording some government officials over others.

Read more at Law.com.

This could be interesting, or maybe impossible.

https://www.nbcnews.com/tech/tech-news/nyc-companies-will-prove-ai-hiring-software-isnt-sexist-racist-rcna92336

In NYC, companies will have to prove their AI hiring software isn't sexist or racist

… A new law, which takes effect Wednesday, is believed to be the first of its kind in the world. Under New York’s new rule, hiring software that relies on machine learning or artificial intelligence to help employers choose preferred candidates or weed out bad ones — called an automatic employment decision tool, or AEDT — must pass an audit by a third-party company to show it’s free of racist or sexist bias.

Companies that run AI hiring software must also publish those results. Businesses that use third-party AEDT software can no longer legally use such programs if they haven’t been audited.

Perspective.

https://www.bespacific.com/how-chat-based-large-language-models-replicate-the-mechanisms-of-a-psychics-con/

The LLMentalist Effect: how chat-based Large Language Models replicate the mechanisms of a psychic’s con

Out of the Software Crisis – Baldur Bjarnason: “For the past year or so I’ve been spending most of my time researching the use of language and diffusion models in software businesses. One of the issues in during this research—one that has perplexed me—has been that many people are convinced that language models, or specifically chat-based language models, are intelligent. But there isn’t any mechanism inherent in large language models (LLMs) that would seem to enable this and, if real, it would be completely unexplained. LLMs are not brains and do not meaningfully share any of the mechanisms that animals or people use to reason or think. LLMs are a mathematical model of language tokens. You give a LLM text, and it will give you a mathematically plausible response to that text. There is no reason to believe that it thinks or reasons—indeed, every AI researcher and vendor to date has repeatedly emphasised that these models don’t think. There are two possible explanations for this effect:

1. The tech industry has accidentally invented the initial stages a completely new kind of mind, based on completely unknown principles, using completely unknown processes that have no parallel in the biological world.

2. The intelligence illusion is in the mind of the user and not in the LLM itself.

Many AI critics, including myself, are firmly in the second camp. It’s why I titled my book on the risks of generative “AI” The Intelligence Illusion. For the past couple of months, I’ve been working on an idea that I think explains the mechanism of this intelligence illusion. I now believe that there is even less intelligence and reasoning in these LLMs than I thought before. Many of the proposed use cases now look like borderline fraudulent pseudoscience to me…”

Perspective.

https://venturebeat.com/ai/gartner-survey-most-corporate-strategists-find-ai-and-analytics-critical-to-success/

Gartner survey: Most corporate strategists find AI and analytics critical to success

A new survey conducted by Gartner has revealed that as many as 79% of global corporate strategists see AI, analytics and automation as critical drivers for success over the next two years.

Conducted between October 2022 and April 2023, the poll highlights enterprises’ growing focus on next-gen technologies. Now, companies are looking at advanced systems not only to handle repetitive or basic tasks but also high-value projects directly related to business growth, such as strategic planning and decision-making.

Resource.

https://mashable.com/uk/deals/ethical-hacking-free-courses

10 of the best ethical hacking courses you can take online for free

… Ethical hacking is the practise of learning the skills of a hacker, but using those skills to highlight system vulnerabilities and implement robust cybersecurity protocols. It's like fighting fire with fire. By understanding the ways of a hacker, you can stay one step ahead of the bad guys.

Inevitable result of training AI on an increasing volume of AI generated data.

https://www.schneier.com/blog/archives/2023/07/class-action-lawsuit-for-scraping-data-without-permission.html

Class-Action Lawsuit for Scraping Data without Permission

I have mixed feelings about this class-action lawsuit against OpenAI and Microsoft, claiming that it “scraped 300 billion words from the internet” without either registering as a data broker or obtaining consent. On the one hand, I want this to be a protected fair use of public data. On the other hand, I want us all to be compensated for our uniquely human ability to generate language.

There’s an interesting wrinkle on this. A recent paper showed that using AI generated text to train another AI invariably “causes irreversible defects.” From a summary:

The tails of the original content distribution disappear. Within a few generations, text becomes garbage, as Gaussian distributions converge and may even become delta functions. We call this effect model collapse.

Just as we’ve strewn the oceans with plastic trash and filled the atmosphere with carbon dioxide, so we’re about to fill the Internet with blah. This will make it harder to train newer models by scraping the web, giving an advantage to firms which already did that, or which control access to human interfaces at scale. Indeed, we already see AI startups hammering the Internet Archive for training data.

This is the same idea that Ted Chiang wrote about: that ChatGPT is a “blurry JPEG of all the text on the Web.” But the paper includes the math that proves the claim.

What this means is that text from before last year—text that is known human-generated—will become increasingly valuable

Somehow I think Meta will find a way to peek…

https://techcrunch.com/2023/07/04/cjeu-meta-superprofiling-decision/

CJEU ruling on Meta referral could close the chapter on surveillance capitalism

Mark your calendar European friends: July 4th could soon be celebrated as independence-from-Meta’s-surveillance-capitalism-day… A long-anticipated judgement handed down today by the Court of Justice of the European Union (CJEU) looks to have comprehensively crushed the social media giant’s ability to keep flouting EU privacy law by denying users a free choice over its tracking and profiling.

The ruling tracks back to a pioneering order by Germany’s antitrust watchdog, the Federal Cartel Office (FCO), which spent years investigating Facebook’s business — making the case that privacy harm should be treated as an exploitative competition abuse too.

Perspective.

https://www.bespacific.com/artificial-intelligence-in-science/

Artificial Intelligence in Science

Artificial Intelligence in Science – Challenges, Opportunities and the Future of Research [300 page e-book available free via OECD]: “The rapid advances of artificial intelligence (AI) in recent years have led to numerous creative applications in science. Accelerating the productivity of science could be the most economically and socially valuable of all the uses of AI. Utilising AI to accelerate scientific productivity will support the ability of OECD countries to grow, innovate and meet global challenges, from climate change to new contagions. This publication is aimed at a broad readership, including policy makers, the public, and stakeholders in all areas of science. It is written in non-technical language and gathers the perspectives of prominent researchers and practitioners. The book examines various topics, including the current, emerging, and potential future uses of AI in science, where progress is needed to better serve scientific advancements, and changes in scientific productivity. Additionally, it explores measures to expedite the integration of AI into research in developing countries. A distinctive contribution is the book’s examination of policies for AI in science. Policy makers and actors across research systems can do much to deepen AI’s use in science, magnifying its positive effects, while adapting to the fast-changing implications of AI for research governance.”

Ingenious! Identify and locate specific soldiers, see what buildings they enter, learn where they live.

https://www.cpomagazine.com/cyber-security/unsolicited-smartwatches-mailed-to-us-military-personnel-raise-security-concerns/

Unsolicited Smartwatches Mailed to US Military Personnel Raise Security Concerns

The U.S. Department of the Army Criminal Investigation Division (CID) has warned about unsolicited smartwatches mailed to US military service members by unknown senders.

… Location-enabled smart devices and apps have leaked military personnel’s location in the past, prompting their restriction in protected areas.

The Army CID has warned service members against powering on the smartwatches that auto-connect to Wi-Fi and pair with cell phones unprompted, potentially accessing a myriad of user data.

My data is Google’s data now? After 17 years of blogging, they change the rules? Should I sue for compensation? Perhaps I should start a misinformation campaign. (You know Google was invented by Hitler in 1933 and was used to coordinate the Holocaust.)

https://gizmodo.com/google-says-itll-scrape-everything-you-post-online-for-1850601486

Google Says It'll Scrape Everything You Post Online for AI

Google updated its privacy policy over the weekend, explicitly saying the company reserves the right to scrape just about everything you post online to build its AI tools. If Google can read your words, assume they belong to the company now, and expect that they’re nesting somewhere in the bowels of a chatbot.

“Google uses information to improve our services and to develop new products, features and technologies that benefit our users and the public,” the new Google policy says. “For example, we use publicly available information to help train Google’s AI models and build products and features like Google Translate, Bard, and Cloud AI capabilities.”

Cheaper is gooder? I think I could live with one of these.

https://techcrunch.com/2023/07/03/jio-bharat-specifications-price-plans/

Ambani’s Jio unveils $12 4G phone with digital pay and streaming

… The Jio Bharat is priced at 999 Indian rupees, or $12.2, Reliance said. The Jio Bharat is designed for 250 million consumers in India who have found the transition to 4G network prohibitively expensive, the Indian giant said. The handset is part of the offering; the other play is the new affordable tariff plan.

Jio Platform unveiled a new monthly plan that costs just 123 Indian rupees, or $1.5 that offers 14GB of data usage for the month and unlimited voice calls. For those subscribing for the year, the plan costs 1,234 Indian rupees, or $15.

Cheaper to shut down rather than comply?

https://www.theverge.com/2023/7/3/23782776/pornhub-blocks-mississippi-virginia-age-verification-laws

Pornhub blocks access in Mississippi and Virginia over age verification laws

Pornhub is now blocking people in Mississippi and Virginia from visiting its website over laws that would require the service to verify their age. The company says it’s blocking users to protest unfair enforcement of these new laws, claiming that sites enforcing the new rules will lose traffic to “irresponsible platforms” that “don’t follow the law, that don’t take user safety seriously, and that often don’t even moderate content.”

Traffic dropped by 80 percent for Pornhub after it began enforcing age verification in Louisiana earlier this year, the company writes. After that experience, it decided to start taking its sites offline instead of enforcing an age gate. In May, it blocked access to users in Utah over a similar law. Techdirt reports that the blackout also applies to other websites operated by Pornhub’s owner, such as RedTube.

Useful overview?

https://www.marktechpost.com/2023/07/03/ai-vs-predictive-analytics-a-comprehensive-analysis/

AI vs. Predictive Analytics: A Comprehensive Analysis

Artificial Intelligence (AI) and Predictive Analytics are reshaping the way all businesses operate. In this article, we will key in on engineering applications of AI and Predictive Analytics. We will start with the general concept of Artificial Intelligence (AI). We’ll go into the details of Predictive Engineering Analytics applied to engineering.

We will give details of Artificial Intelligence approaches such as Machine Learning and Deep Learning. Key differences will be highlighted. By the end of the article, you will understand how innovative Deep Learning technology leverages historical data and accurately forecasts outcomes of lengthy and expensive experimental testing or 3D simulation (CAE).

Tools & Techniques. Everyone can use the first tool!

https://www.makeuseof.com/data-scientists-best-chrome-extensions/

The 5 Best Chrome Extensions for Data Scientists

… As with any complex task, you should look for tools to make your job easier and more enjoyable. Here are some powerful Chrome extensions to help boost your productivity, whether you’re a new or experienced data scientist.

Insider attack? Is Russia falling apart?

https://www.databreaches.net/cyberattack-knocks-out-satellite-communications-for-russian-military/

Cyberattack knocks out satellite communications for Russian military

Joseph Menn reports:

A satellite communications system serving the Russian military was knocked offline by a cyberattack late Wednesday and remained mostly down on Thursday, in an incident reminiscent of an attack on a similar system used by Ukraine at the start of the war between the countries.

Dozor-Teleport, the satellite system’s operator, switched some users to terrestrial networks during the outage, according to JD Work, a cyberspace professor at the National Defense University.

Read more at The Washington Post.

A Wagner-affiliated group claimed responsibility for the attack.

Vague laws make for many lawsuits?

https://www.theregister.com/2023/07/03/china_espionage_law_update_warning/

US authorities warn on China's new counter-espionage law

Almost anything you download from China could be considered spying, but at least one analyst isn't worried

The United States' National Counterintelligence and Security Center (NCSC) has warned that China's updated Counter-Espionage law – which came into effect on July 1 – is dangerously ambiguous and could pose a risk to global business.

The NCSC publishes non-classified bulletins titled "Safeguarding Our Future" on an ad hoc schedule to "provide a brief overview of a specific foreign intelligence threat, as well as impacts of that threat and steps for mitigation."

On June 30 it issued a new one [PDF] titled "US Business Risk: People's Republic of China (PRC) Laws Expand Beijing's Oversight of Foreign and Domestic Companies." The first item discussed is China's recently revised Counter-Espionage Law, on grounds it "Expands the definition of espionage from covering state secrets and intelligence to any documents, data, materials, or items related to national security interests, without defining terms."

That vagueness, the Center argues, means "Any documents, data, materials, or items could be considered relevant to PRC national security due to ambiguities in the law" and adds up to potential "legal risks or uncertainty for foreign companies."

Perspective. Economics as history...

https://www.ben-evans.com/benedictevans/2023/7/2/working-with-ai

AI and the automation of work

ChatGPT and generative AI will change how we work, but how different is this to all the other waves of automation of the last 200 years? What does it mean for employment? Disruption? Coal consumption?

… The Lump of Labour fallacy is the misconception that there is a fixed amount of work to be done, and that if some work is taken by a machine then there will be less work for people. But if it becomes cheaper to use a machine to make, say, a pair of shoes, then the shoes are cheaper, more people can buy shoes and they have more money to spend on other things besides, and we discover new things we need or want, and new jobs.

… In the 19th century the British navy ran on coal. Britain had a lot of coal (it was the Saudi Arabia of the steam age) but people worried what would happen when the coal ran out. Ah, said the engineers: don’t worry, because the steam engines keep getting more efficient, so we’ll use less coal. No, said Jevons: if we make steam engines more efficient, then they will be cheaper to run, and we will use more of them and use them for new and different things, and so we will use more coal.

We’ve been applying the Jevons Paradox to white collar work for 150 years.

Perspective.

https://www.insideprivacy.com/artificial-intelligence/uk-and-g7-privacy-authorities-warn-of-privacy-risks-raised-by-generative-ai/

UK and G7 Privacy Authorities Warn of Privacy Risks Raised by Generative AI

On 21 June 2023, at the close of a roundtable meeting of the G7 Data Protection and Privacy Authorities, regulators from the United States, France, Germany, Italy, United Kingdom, Canada and Japan published a joint “Statement on Generative AI” (“Statement”) (available here ). In the Statement, regulators identify a range of data protection-related concerns they believe are raised by generative AI tools, including legal authority for processing personal information, and transparency, explainability, and security. The group of regulators also call on companies to “embed privacy in the design conception, operation, and management” of generative AI tools.

Interesting. A useful model for other industries?

https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4488199

Embracing Artificial Intelligence in the Legal Landscape: The Blueprint

This innovative case study outlines a blueprint for strategic transformation based on the example of a real-life law firm operating in Germany, using AI tools and digitalization. Leveraging Kotter's 8-step change model, the research underscores the imperative to adopt AI due to pressing market competition and escalating internal costs. The paper articulates how AI can optimize legal processes and dramatically improve efficiency and client satisfaction, while addressing the firm's readiness to adapt and potential resistance.

By building a coalition of key stakeholders and envisioning the firm's future as a technology-driven entity, this research elucidates a pragmatic roadmap for the firm's digital journey.

The conclusion suggests a pivotal shift toward a culture that celebrates change and fosters growth, strengthening the firm's competitive position and enabling sustainable success in the ever-evolving legal landscape.

Does all the training data have to pass an ethics review before it can be used safely?

https://link.springer.com/article/10.1007/s00429-023-02662-7

The human cost of ethical artificial intelligence

Foundational models such as ChatGPT critically depend on vast data scales the internet uniquely enables. This implies exposure to material varying widely in logical sense, factual fidelity, moral value, and even legal status. Whereas data scaling is a technical challenge, soluble with greater computational resource, complex semantic filtering cannot be performed reliably without human intervention: the self-supervision that makes foundational models possible at least in part presupposes the abilities they seek to acquire. This unavoidably introduces the need for large-scale human supervision—not just of training input but also model output—and imbues any model with subjectivity reflecting the beliefs of its creator. The pressure to minimize the cost of the former is in direct conflict with the pressure to maximise the quality of the latter. Moreover, it is unclear how complex semantics, especially in the realm of the moral, could ever be reduced to an objective function any machine could plausibly maximise. We suggest the development of foundational models necessitates urgent innovation in quantitative ethics and outline possible avenues for its realisation.

Tools & Techniques. ChatGPT responds after searching for ‘appropriate’ chunks of data in its training data. If you asked for a ‘new recipe for cornbread’ there might be hundreds of articles with new in the title. How would it ever come up with something really new?

https://www.businessinsider.com/how-to-use-get-better-chatgpt-ai-prompt-guide

12 ways to get better at using ChatGPT: Comprehensive prompt guide

… ChatGPT doesn't always produce desirable outcomes, and the tech can be prone to errors and misinformation.

It all comes down to the prompts users put into ChatGPT.

"If you really want to generate something that is going to be useful for you, you need to do more than just write a generic sentence," Jacqueline DeStefano-Tangorra, a consultant who uses ChatGPT to secure new contracts, told Insider.