In short, you can talk (prompt) the LLM into including or excluding certain data, changing the output.

https://www.schneier.com/blog/archives/2023/03/prompt-injection-attacks-on-large-language-models.html

Prompt Injection Attacks on Large Language Models

This is a good survey on prompt injection attacks on large language models (like ChatGPT).

Abstract: We are currently witnessing dramatic advances in the capabilities of Large Language Models (LLMs). They are already being adopted in practice and integrated into many systems, including integrated development environments (IDEs) and search engines. The functionalities of current LLMs can be modulated via natural language prompts, while their exact internal functionality remains implicit and unassessable. This property, which makes them adaptable to even unseen tasks, might also make them susceptible to targeted adversarial prompting. Recently, several ways to misalign LLMs using Prompt Injection (PI) attacks have been introduced. In such attacks, an adversary can prompt the LLM to produce malicious content or override the original instructions and the employed filtering schemes. Recent work showed that these attacks are hard to mitigate, as state-of-the-art LLMs are instruction-following. So far, these attacks assumed that the adversary is directly prompting the LLM.

In this work, we show that augmenting LLMs with retrieval and API calling capabilities (so-called Application-Integrated LLMs) induces a whole new set of attack vectors. These LLMs might process poisoned content retrieved from the Web that contains malicious prompts pre-injected and selected by adversaries. We demonstrate that an attacker can indirectly perform such PI attacks. Based on this key insight, we systematically analyze the resulting threat landscape of Application-Integrated LLMs and discuss a variety of new attack vectors. To demonstrate the practical viability of our attacks, we implemented specific demonstrations of the proposed attacks within synthetic applications. In summary, our work calls for an urgent evaluation of current mitigation techniques and an investigation of whether new techniques are needed to defend LLMs against these threats.

(Related)

https://sloanreview.mit.edu/article/the-no-1-question-to-ask-when-evaluating-ai-tools/

The No. 1 Question to Ask When Evaluating AI Tools

In the fast-moving and highly competitive artificial intelligence sector, developers’ claims that their AI tools can make critical predictions with a high degree of accuracy are key to selling prospective customers on their value. Because it can be daunting for people who are not AI experts to evaluate these tools, leaders may be tempted to rely on the high-level performance metrics published in sales materials. But doing so often leads to disappointing or even risky implementations.

Over the course of an 11-month investigation, we observed managers in a leading health care organization as they conducted internal pilot studies of five AI tools. Impressive performance results had been promised for each, but several of the tools did extremely poorly in their pilots. Analyzing the evaluation process, we found that an effective way to determine an AI tool’s quality is understanding and examining its ground truth.1 In this article, we’ll explain what that is and how managers can dig into it to better assess whether a particular AI tool may enhance or diminish decision-making in their organization.

Tools & Techniques.

https://beebom.com/how-build-own-ai-chatbot-with-chatgpt-api/

How to Build Your Own AI Chatbot With ChatGPT API: A Step-by-Step Tutorial

In a breakthrough announcement, OpenAI recently introduced the ChatGPT API to developers and the public. Particularly, the new “gpt-3.5-turbo” model, which powers ChatGPT Plus has been released at a 10x cheaper price, and it’s extremely responsive as well. Basically, OpenAI has opened the door for endless possibilities and even a non-coder can implement the new ChatGPT API and create their own AI chatbot. So in this article, we bring you a tutorial on how to build your own AI chatbot using the ChatGPT API. We have also implemented a Gradio interface so you can easily demo the AI model and share it with your friends and family. On that note, let’s go ahead and learn how to create a personalized AI with ChatGPT API.

Do I need to be worried?

https://www.businessinsider.com/florida-blogger-registration-bill-violates-first-amendment-aclu-2023-3

A proposed law that would require people blogging about Ron DeSantis to register with the state is a 'clear violation of the First Amendment:' ACLU

A Florida lawmaker has introduced a bill that would require all bloggers who write about Gov. Ron DeSantis to register with the state or be fined. Organizations like the ACLU tell Insider that the proposed law violates the right to free speech.

A representative for the American Civil Liberties Union's Florida chapter told Insider the bill, S.B. 1316, is "un-American to its core."

"This is a clear violation of the First Amendment because it strongly discourages bloggers from speaking on politics – one of the most critical types of speech for maintaining a democracy," the ACLU representative told Insider.

Better than I feared, but I’d like some examples.

https://techpolicy.press/on-facebook-visual-misinfo-widespread-highly-asymmetric-across-party-lines/

On Facebook, Visual Misinfo Widespread, Highly Asymmetric Across Party Lines

… In “Visual misinformation on Facebook,” published this week in the Journal of Communication, scholars from Texas A&M University’s Department of Communication & Journalism, Columbia University’s Tow Center for Digital Journalism, and the George Washington University’s Institute for Data, Democracy & Politics collected and analyzed nearly 14 million posts from more than 14,000 pages and 11,000 public groups from August through October 2020.

From this corpus, the researchers arrived at a representative data set of political images, and another of images that specifically depicted political figures. An analysis found that 23% of political images in a sample contained misinformation, while 20% of those that depicted a political figure were misleading.

Surveillance is not just a people thing.

https://timesofindia.indiatimes.com/world/china/trojan-horse-why-us-officials-have-raised-alarm-over-giant-chinese-cargo-cranes/articleshow/98449335.cms

'Trojan horse': Why US officials have raised alarm over giant Chinese cargo cranes

Ever since US shot down a giant Chinese surveillance balloon over its airspace last month, there has been heightened global scrutiny on the scale of Beijing's spying operations.

Now, American officials have raised concerns over the possibility of a "new tool" of spying hiding in plain sight: giant Chinese-made cranes operating at US ports.

According to a report in the Wall Street Journal (WSJ), Pentagon officials suspect that cranes made by Chinese manufacturer ZPMC operating at ports across America are being used to register sensitive information.

… They said that these cranes contain sophisticated sensors which can register and track the provenance and destination of containers, enabling China to capture information about materiel being shipped in or out of US to support its military operations around the world, the report said.

Perspective.

https://www.computerweekly.com/news/365531613/AI-interview-Michael-Osborne-professor-of-machine-learning

AI interview: Michael Osborne, professor of machine learning

… A key theme of his overall research has been the societal and economic impacts of new technologies, particularly with regards to automation of the workplace.

Speaking with Computer Weekly, Osborne notes the pressing need to wrest control of AI’s development and deployment away from corporations in the private sector, so that it can be used to its full potential in promoting human flourishing.

“It’s fair to say that the private sector has been a bit too powerful when it comes to AI…if we want to see the benefits of these technologies, states need to step in to unlock and to drain some of the moats that are protecting big tech,” he says.

To achieve this, he argues for tighter guardrails on what the private sector can do with AI and for a rebalancing of the scales in favour of public research institutions. Osborne also says there should be serious thought given to how political processes can be used to change the direction of travel with AI.

But the computer said it was okay!

https://link.springer.com/article/10.1007/s10506-023-09347-w

Going beyond the “common suspects”: to be presumed innocent in the era of algorithms, big data and artificial intelligence

This article explores the trend of increasing automation in law enforcement and criminal justice settings through three use cases: predictive policing, machine evidence and recidivism algorithms. The focus lies on artificial-intelligence-driven tools and technologies employed, whether at pre-investigation stages or within criminal proceedings, in order to decode human behaviour and facilitate decision-making as to whom to investigate, arrest, prosecute, and eventually punish. In this context, this article first underlines the existence of a persistent dilemma between the goal of increasing the operational efficiency of police and judicial authorities and that of safeguarding fundamental rights of the affected individuals. Subsequently, it shifts the focus onto key principles of criminal procedure and the presumption of innocence in particular. Using Article 6 ECHR and the Directive (EU) 2016/343 as a starting point, it discusses challenges relating to the protective scope of presumption of innocence, the burden of proof rule and the in dubio pro reo principle as core elements of it. Given the transformations law enforcement and criminal proceedings go through in the era of algorithms, big data and artificial intelligence, this article advocates the adoption of specific procedural safeguards that will uphold rule of law requirements, and particularly transparency, fairness and explainability. In doing so, it also takes into account EU legislative initiatives, including the reform of the EU data protection acquis, the E-evidence Proposal, and the Proposal for an EU AI Act. Additionally, it argues in favour of revisiting the protective scope of key fundamental rights, considering, inter alia, the new dimensions suspicion has acquired.

Which ethic?

https://ui.adsabs.harvard.edu/abs/2023arXiv230212149K/abstract

Beyond Bias and Compliance: Towards Individual Agency and Plurality of Ethics in AI

AI ethics is an emerging field with multiple, competing narratives about how to best solve the problem of building human values into machines. Two major approaches are focused on bias and compliance, respectively. But neither of these ideas fully encompasses ethics: using moral principles to decide how to act in a particular situation. Our method posits that the way data is labeled plays an essential role in the way AI behaves, and therefore in the ethics of machines themselves. The argument combines a fundamental insight from ethics (i.e. that ethics is about values) with our practical experience building and scaling machine learning systems. We want to build AI that is actually ethical by first addressing foundational concerns: how to build good systems, how to define what is good in relation to system architecture, and who should provide that definition. Building ethical AI creates a foundation of trust between a company and the users of that platform. But this trust is unjustified unless users experience the direct value of ethical AI. Until users have real control over how algorithms behave, something is missing in current AI solutions. This causes massive distrust in AI, and apathy towards AI ethics solutions. The scope of this paper is to propose an alternative path that allows for the plurality of values and the freedom of individual expression. Both are essential for realizing true moral character.

Yes, this again. Cutting the AI out of the benefits?

https://digitalcommons.law.scu.edu/chtlj/vol39/iss2/2/

RECONCEPTUALIZING CONCEPTION: MAKING ROOM FOR ARTIFICIAL INTELLIGENCE INVENTIONS

Artificial intelligence (AI) enables the creation of inventions that no natural person conceived, at least as conception is traditionally understood in patent law. These can be termed “AI inventions,” i.e., inventions for which an AI system has contributed to the conception in a manner that, if the AI system were a person, would lead to that person being named as an inventor. Deeming such inventions unpatentable would undermine the incentives at the core of the patent system, denying society access to the full benefits of the extraordinary potential of AI systems with respect to innovation. But naming AI systems as inventors and allowing patentability on that basis is also problematic, as it involves granting property rights to computer programs. This Article proposes a different approach: AI inventions should be patentable, with inventorship attributed to the natural persons behind the AI under a broadened view of conception. More specifically, conception should encompass ideas formed through collaboration between a person and tools that act as extensions of their mind. The “formation” of those ideas should be attributed to the person, including when the ideas underlying the invention were first expressed by a tool used to enhance their creative capacity and subsequently conveyed to them.

Automating a task humans could do poorly?

https://www.latimes.com/politics/story/2023-03-03/surveillance-ai-coappearance-facial-recognition

The cameras know who you are. Now they want to use AI to find your friends too

Local interest.

https://www.databreaches.net/hacker-stole-bank-account-social-security-numbers-and-health-plan-info-of-colorado-school-district-employees/

Hacker stole bank account, Social Security numbers, and health plan info of Colorado school district employees

Nate Lynn reports:

Personal information belonging to some 15,000 Denver Public Schools (DPS) employees was stolen in what the district is calling a “cybersecurity incident” that went on for a month.

In a message shared on the DPS website Friday, DPS said employees discovered in January that data had been taken from the district’s network by an “unauthorized actor.”

[…]

The information stolen included the names and Social Security numbers of current and former participants in the DPS employee health plan, employee fingerprints, bank account numbers or pay card numbers, driver’s license numbers, passport numbers and health plan enrollment information.

Read more at 9News.

Worth considering?

https://www.investing.com/analysis/is-artificial-intelligence-the-next-bubble-200635861

Is Artificial Intelligence the Next Bubble?

In this article, we will look at the 5 stages of a financial bubble, suggesting AI may already be entering phase 2.

Perhaps we all should RTFM?

https://www.newscientist.com/article/2358953-ai-masters-video-game-6000-times-faster-by-reading-the-instructions/

AI masters video game 6000 times faster by reading the instructions

An artificial intelligence has learned to master an Atari skiing game in days of playing time rather than the decades it took a specialist DeepMind AI, simply by reading the instructions written for humans before it started

Another case of “We can, therefore we must?” (I have a new hammer, let’s find some nails!)

https://www.pogowasright.org/report-ice-and-the-secret-service-conducted-illegal-surveillance-of-cell-phones/

Report: ICE and the Secret Service Conducted Illegal Surveillance of Cell Phones

Mathew Guariglia of EFF writes:

The Department of Homeland Security’s Inspector General has released a troubling new report detailing how federal agencies like Immigration and Customs Enforcement (ICE), Homeland Security Investigations (HSI), and the Secret Service have conducted surveillance using cell-site simulators (CSS) without proper authorization and in violation of the law. Specifically, the office of the Inspector General found that these agencies did not adhere to federal privacy policy governing the use of CSS and failed to obtain special orders required before using these types of surveillance devices.

Even under exigent circumstances, where law enforcement use of technologies that track cell-phone use are deemed immediately necessary, law enforcement must still get a pen register order. The pen register order is required by statute and policy even though exigency otherwise excuses police from having to obtain a conventional warrant. The Inspector General noted that the agencies didn’t follow the rules in these cases either.

Cell-site simulators, also known as “Stingrays” or IMSI catchers, are devices that masquerade as legitimate cell-phone towers, tricking phones within a certain radius into connecting to the device rather than a tower.

Cell-site simulators operate by conducting a general search of all cell phones within the device’s radius, in violation of basic constitutional protections. Law enforcement use cell-site simulators to pinpoint the location of phones with greater accuracy than phone companies. Cell-site simulators can also log IMSI numbers (unique identifying numbers) of all of the mobile devices within a given area.

Unfortunately, the report redacts crucial information regarding the total number of times that each agency used CSS with and without a warrant, and when they used the devices to support external information. The OIG should release this information to the public: knowing the aggregate totals would not harm any active investigation, but rather inform public debate over the agencies’ reliance on this invasive technology. Make no mistake, cell-site simulators are mass surveillance that draws in the cell signal and collects data on every phone in the vicinity.

The fact that government agencies are using these devices without the utmost consideration for the privacy and rights of individuals around them is alarming but not surprising. The federal government, and in particular agencies like HSI and ICE, have a dubious and troubling relationship with overbroad collection of private data on individuals. In 2022 we learned that HSI and ICE had used overly-broad warrants to collect bulk financial records concerning people sending money across international borders through companies like Western Union. Mass surveillance of this kind is a massive violation of privacy and has elicited the concern of at least one U.S. senator hoping to probe into these tactics.

Most people carry cell phones on them at any given moment. EFF will continue to fight against careless government use of cell-site simulators, and we will continue to monitor federal agencies that rely on secrecy and a strategic ignorance of the law in order to wield powerful and overly broad surveillance powers and technologies.

This column was originally published at EFF.

In related coverage of the IG’s report, Zack Whittaker pulls out some specific examples of concerns, such as:

In one case highlighted by the inspector general, a county judge “did not understand” why prosecutors sought an emergency surveillance order because, not understanding the statute, the judge “believed it to be unnecessary,” leading to a raft of warrantless deployments.

Read more at TechCrunch.

Perspective.

https://krebsonsecurity.com/2023/03/highlights-from-the-new-u-s-cybersecurity-strategy/

Highlights from the New U.S. Cybersecurity Strategy

The Biden administration today issued its vision for beefing up the nation’s collective cybersecurity posture, including calls for legislation establishing liability for software products and services that are sold with little regard for security. The White House’s new national cybersecurity strategy also envisions a more active role by cloud providers and the U.S. military in disrupting cybercriminal infrastructure, and it names China as the single biggest cyber threat to U.S. interests.

(Related)

https://www.csoonline.com/article/3689870/software-liability-reform-is-liable-to-push-us-off-a-cliff.html#tk.rss_all

Software liability reform is liable to push us off a cliff

Like “SBOMs will solve everything,” there is a regular cry to reform software liability, specifically in the case of products with insecurities and vulnerabilities. US Cybersecurity and Infrastructure Security Agency (CISA) Director Jen Easterly’s comments this week brought the topic back into focus, but it’s still a thorny issue. (There’s a reason certain things are called “wicked problems.”) The proposed remedy, taking up a full page of the Biden Administration’s National Cybersecurity Strategy, will cause more problems than it solves.

One of my favorite topics.

https://www.bespacific.com/generative-artificial-intelligence-and-copyright-law/

Generative Artificial Intelligence and Copyright Law

CRS Legal Sidebar – Generative Artificial Intelligence and Copyright Law. February 24, 2023: “Recent innovations in artificial intelligence (AI) are raising new questions about how copyright law principles such as authorship, infringement, and fair use will apply to content created or used by AI. So-called “generative AI” computer programs—such as Open AI’s DALL-E 2 and ChatGPT programs, Stability AI’s Stable Diffusion program, and Midjourney’s self-titled program—are able to generate new images, texts, and other content (or “outputs”) in response to a user’s textual prompts (or “inputs”). These generative AI programs are “trained” to generate such works partly by exposing them to large quantities of existing works such as writings, photos, paintings, and other artworks. This Legal Sidebar explores questions that courts and the U.S. Copyright Office have begun to confront regarding whether the outputs of generative AI programs are entitled to copyright protection as well as how training and using these programs might infringe copyrights in other works.”

Perspective.

https://www.newsmax.com/finance/streettalk/artificial-intelligence-market-future-technology/2023/03/01/id/1110607/

AI on Brink of Revolution Akin to the iPhone

Artificial intelligence is on the brink of a revolutionary “iPhone moment” whereby it will boost the world economy by $15.7 trillion by 2030, Bank of America strategists predict.

In a Tuesday note to clients, BofA list four reasons why AI will transform industries, as Business Insider reports.

The four driving factors driving the AI revolution:

• Democratization of data

• Unprecedented mass adoption

• Warp-speed technological development

• Abundant commercial uses

Another perspective.

https://techpolicy.press/ten-legal-and-business-risks-of-chatbots-and-generative-ai/

Ten Legal and Business Risks of Chatbots and Generative AI

… The technology is advancing at a breakneck speed. As Axios put it, “The tech industry isn’t letting fears about unintended consequences slow the rush to deploy a new technology.” That approach is good for innovation, but it poses its own challenges. As generative AI advances, companies will face a number of legal and ethical risks, both from malicious actors leveraging this technology to harm businesses and when businesses themselves wish to implement chatbots or other forms of AI into their functions.

This is a quickly developing area, and new legal and business dangers—and opportunities—will arise as the technology advances and use cases emerge. Government, business and society can take the early learnings from the explosive popularity of generative AI to develop guardrails to protect against their worst behavior and use cases before this technology pervades all facets of commerce. To that end, businesses should be aware of the following top 10 risks and how to address them.

An aspect of ‘self-driving’ that I had not considered.

https://www.businessinsider.com/ford-patent-cars-repossess-themselves-drive-away-if-missing-payments-2023-2

Ford wants to allow your car to lock you out — and even drive itself to an impound lot or scrapyard — if you miss payments

Not sure I agree, but interesting.

https://bigthink.com/the-future/hyperwar-ai-military-warfare/

“Hyperwar”: How AI could cause wars to spiral out of human control

• Four Battlegrounds by Paul Scharre explores the competition between AI superpowers and the four key elements that define this struggle: data, computing power, talent, and institutions.

• This book excerpt explains how artificial intelligence could soon change how militaries fight on the battlefield.

• AI could transform battle tactics to the extent that humans can't keep up with it — a scenario which Scharre refers to as a "singularity" in warfare.

Resources.

https://mashable.com/uk/deals/learn-ai-for-free

Learn how to use AI with the best free online courses on Udemy

A wide range of online courses on artificial intelligence are available for free on Udemy. You don't need a voucher code to access these courses for free, and you can learn at your own pace.

I suspect they tripped over a vulnerability rather than made a deliberate choice to hack the Marshals. Unfortunately, the results are the same.

https://www.cnn.com/2023/02/27/politics/us-marshals-service-ransomeware-attack/index.html

Ransomware attack on US Marshals Service affects ‘law enforcement sensitive information’

A ransomware attack on the US Marshals Service has affected a computer system containing “law enforcement sensitive information,” including personal information belonging to targets of investigations, a US Marshals Service spokesperson said Monday evening.

… The Justice Department subsequently determined it “constitutes a major incident,” according to the statement. A “major incident” is a hack that is significant enough that it requires a federal agency to notify Congress.

Can we identify the irrelevant, then eliminate it? Perhaps we need another AI?

https://www.bespacific.com/large-language-models-can-be-easily-distracted-by-irrelevant-context/

Large Language Models Can Be Easily Distracted by Irrelevant Context

Large Language Models Can Be Easily Distracted by Irrelevant Context. Freda Shi, Xinyun Chen, Kanishka Misra, Nathan Scales, David Dohan, Ed Chi, Nathanael Schärli, Denny Zhou. [current version in PDF ]

“Large language models have achieved impressive performance on various natural language processing tasks. However, so far they have been evaluated primarily on benchmarks where all information in the input context is relevant for solving the task. In this work, we investigate the distractibility of large language models, i.e., how the model problem-solving accuracy can be influenced by irrelevant context. In particular, we introduce Grade-School Math with Irrelevant Context (GSM-IC), an arithmetic reasoning dataset with irrelevant information in the problem description. We use this benchmark to measure the distractibility of cutting-edge prompting techniques for large language models, and find that the model performance is dramatically decreased when irrelevant information is included. We also identify several approaches for mitigating this deficiency, such as decoding with self-consistency and adding to the prompt an instruction that tells the language model to ignore the irrelevant information.”

Idiotic? Our current political environment.

https://www.bespacific.com/texas-asks-trump-judge-to-declare-most-of-federal-government-unconstitutional/

Texas asks Trump judge to declare most of federal government unconstitutional

Vox: “Earlier this month, Texas’s Republican Attorney General Ken Paxton filed a lawsuit claiming that the $1.7 trillion spending law that keeps most of the federal government — including the US military — operating through September of 2023 is unconstitutional. Paxton’s claims in Texas v. Garland, which turn on the fact that many of the lawmakers who voted for the bill voted by proxy, should fail. They are at odds with the Constitution’s explicit text. And a bipartisan panel of a powerful federal appeals court in Washington, DC, already rejected a similar lawsuit in 2021. Realistically, this lawsuit is unlikely to prevail even in the current, highly conservative Supreme Court. Declaring a law that funds most of the federal government unconstitutional would be an extraordinary act, especially given the very strong legal arguments against Paxton’s position. But the case is a window into Paxton’s broader litigation strategy, where he frequently raises weak legal arguments undercutting federal policies before right-wing judges that he has personally chosen because of their ideology. And these judges often do sow chaos throughout the government, which can last months or longer, before a higher court steps in. Texas’s federal courts give plaintiffs an unusual amount of leeway to choose which judge will hear their case. an odd feature of these courts that Paxton often takes advantage of to ensure that his lawsuits will be heard by judges who are likely to toe the Republican line. These decisions, moreover, appeal to the deeply conservative United States Court of Appeals for the Fifth Circuit. Paxton filed the Garland case in Lubbock, Texas, where 100 percent of all federal lawsuits are heard by a Republican appointee. Two-thirds of such cases are automatically assigned to Judge James Wesley Hendrix, who will hear this suit. Hendrix, a Trump appointee to a federal court in Texas, is a bit of an unknown quantity. In his brief time on the bench, Hendrix did hand down one poorly reasoned decision undercutting a federal statute that requires most hospitals to perform medically necessary abortions. But Hendrix’s thin record does not tell us enough to know whether he’d actually be so aggressive as to declare most of the United States government unconstitutional…”

A bit simplistic?

https://fee.org/articles/how-the-ai-wars-are-proving-that-google-isnt-a-monopoly/

How the AI Wars Are Proving That Google Isn't a Monopoly

If Google is really a monopoly, why would investors be worried about a competitor developing a new product?

Google’s share price dropped nearly 10 percent earlier this month in the wake of Microsoft’s announcement that they are integrating Open AI’s ChatGPT into their search engine. Microsoft’s search engine, Bing, currently accounts for only three percent of web searches, trailing far behind Google’s impressive market share of more than 90 percent. Google’s dominance in search is so total, and has been stable for so long, that it has led many to accuse Google of being a monopoly.

Claims of monopoly are common in political discourse, and they have been made against Google by all sides of the political compass. In 2020, Senator Ted Cruz accused Google of using its “monopoly” power to stifle conservative voices. In 2019, Senator Bernie Sanders expressed his desire to break Google up over its alleged monopoly status. In January of this year, the Justice Department sued Google for “monopolizing” digital advertising, which is the way Google monetizes its search service.

(Related) and more interesting…

https://www.washingtonpost.com/technology/2023/02/26/antitrust-google-doj-tech/

Biden finds breaking up Big Tech is hard to do

Google is hiring teams of former DOJ lawyers to fight antitrust lawsuits as the battle over tech firms’ power shifts to the courts

Google has been quietly assembling a phalanx of former Justice Department lawyers as the tech titan gears up for the regulatory fight of its life against the attorneys’ former employer.

The Department of Justice offensive, a pair of lawsuits aimed at breaking up the search giant’s dominance, will play out in the courts — reflecting a new phase in the Biden administration’s years-long effort to rein in Big Tech, after a sweeping antitrust package stalled in Congress.

Because… (Or download them into Calibre and read them anywhere.)

https://www.makeuseof.com/tag/classic-novels-read-free-kindle/

35 Classic Novels You Can Read for Free on Your Kindle

There's a treasure trove of free books available on to download to your Kindle. Here are our recommendations for classic novels you should read.

Always interesting.

https://www.rand.org/content/dam/rand/pubs/research_reports/RRA2200/RRA2249-1/RAND_RRA2249-1.pdf

Finding a Broadly Practical Approach for Regulating the Use of Facial Recognition by Law Enforcement

Communities across the United States are grappling with the implications of law enforcement organizations’ and other government agencies’ use of facial recognition (FR) technology. Although the purported benefits of FR as stated are clear, they have yet to be measured and weighed against the existing risks, which are also substantial. Given the variety of ways in which FR can be used by law enforcement, the full benefit-to-risk trade-off is difficult to account for, leading to some municipalities that ban the use of FR by law enforcement and others that have no clear regulations. This report provides an overview of what is known about FR use in law enforcement and provides a road map of sorts to help policymakers sort through the various risks and benefits relative to different types of FR use.

We categorize the various identified risks associated with FR technology and its use by law enforcement, including accuracy, bias, the scope of the search (i.e., surveillance versus investigation), data-sharing and storage practices, privacy issues, human and civil rights, officer misuse, law enforcement reactions to the FR results (e.g., street stops), public acceptance, and unintended consequences. The concerns are discussed in detail in Chapter 3, but they are summarized here.

A thoughtful AI?

https://www.tandfonline.com/doi/full/10.1080/15027570.2023.2180184

The Need for a Commander

… One article in this double issue of the Journal of Military Ethics asks about what an AI (artificial intelligence) commander would look like. The underlying question is whether we are more or less inevitably moving towards a situation where AI-driven systems will come to make strategic decisions and hence be the place where the buck stops.

I don’t get it…

https://www.science.org/doi/abs/10.1126/science.add2202

Leveraging IP for AI governance

The rapidly evolving and expanding use of artificial intelligence (AI) in all aspects of daily life is outpacing regulatory and policy efforts to guide its ethical use (1). Governmental inaction can be explained in part by the challenges that AI poses to traditional regulatory approaches (1). We propose the adaptation of existing legal frameworks and mechanisms to create a new and nuanced system of enforcement of ethics in AI models and training datasets. Our model leverages two radically different approaches to manage intellectual property (IP) rights. The first is copyleft licensing, which is traditionally used to enable widespread sharing of created content, including open-source software. The second is the “patent troll” model, which is often derided for suppressing technological development. Although diametric in isolation, these combined models enable the creation of a “troll for good” capable of enforcing the ethical use of AI training datasets and models.

I think I think so too.

https://indexlaw.org/index.php/rdb/article/view/7547

DEEP LEARNING AND THE RIGHT TO EXPLANATION: TECHNOLOGICAL CHALLENGES TO LEGALITY AND DUE PROCESS OF LAW

This article studies the right to explainability, which is extremely important in times of fast technological evolution and use of deep learning for the most varied decision-making procedures based on personal data. Its main hypothesis is that the right to explanation is totally linked to the due process of Law and legality, being a safeguard for those who need to contest automatic decisions taken by algorithms, whether in judicial contexts, in general Public Administration contexts, or even in private entrepreneurial contexts.. Through hypothetical-deductive procedure method, qualitative and transdisciplinary approach, and bibliographic review technique, it was concluded that opacity, characteristic of the most complex systems of deep learning, can impair access to justice, due process legal and contradictory. In addition, it is important to develop strategies to overcome opacity through the work of experts, mainly (but not only). Finally, Brazilian LGPD provides for the right to explanation, but the lack of clarity in its text demands that the Judiciary and researchers also make efforts to better build its regulation.

Tools worth testing?

https://www.makeuseof.com/accurate-ai-text-detectors/

The 8 Most Accurate AI Text Detectors You Can Try

As language models like GPT continue to improve, it is becoming increasingly difficult to differentiate between AI-generated and human-written text. But, in some cases, like academics, it’s necessary to ensure that the text isn't written by AI.

This is where AI text detectors come into play. Though none of the tools currently available detect with complete certainty (and neither do they claim to do so), a few of these tools do provide pretty accurate results. So, here, we list down the eight most accurate AI text detectors you can try.