According to Model Rule 1.1 of the ABA Model Rules of Professional Conduct: “A lawyer shall provide competent representation to a client. Competent representation requires the legal knowledge, skill, thoroughness and preparation reasonably necessary for the representation.”
In 2012, the ABA House of Delegates voted to amend Comment 8 to Model Rule 1.1 to include explicit guidance on lawyers’ use of technology.
If Model Rule 1.1 isn’t enough of a motivator to dip your feet in legal tech, maybe paying off that mortgage is. As an extra bit of motivation, it may benefit you to pin the ABA House of Delegate’s call to action on your motivation board.
What is different with AI is the scale by which this knowledge is aggregated. While a lawyer who has been before a judge three or four times may have formed some opinions about them, these opinions are based on anecdotal evidence. AI can read the judge’s entire history of decision-making and spit out an argument based on what it finds.
The common law has always used precedents, but what is being used here is different — it’s figuring out how a judge likes an argument to be framed, what language they like using, and feeding it back to them.
And because the legal system builds on itself — with judges using prior cases to determine how a decision should be made in the case before them — these AI-assisted arguments from lawyers could have the effect of further entrenching a judge’s biases in the case law, as the judge’s words are repeated verbatim in more and more decisions. This is particularly true if judges are unaware of their own biases.
Given that we have spent time over the past few years telling people not to get to overestimate the capability of AI, is this the real deal?
“Yeah, I think it’s the real thing because if you look at why legal technologies have not had the adoption rate historically, language has always been the problem,” Katz said. “Language has been hard for machines historically to work with, and language is core to law. Every road leads to a document, essentially.”
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Katz says: “There are two types of things here. They would call general models GPT one through four, and then there’s domain models, so a legal specific large language model.
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“What we’re going to see are large-ish, albeit not the largest model that’s heavily domain tailored is going to beat a general model in the same way that a really smart person can’t beat a super specialist. That’s where the value creation and the next generation of legal technology is going to live.”
The FBI and the Defense Department were actively involved in research and development of facial recognition software that they hoped could be used to identify people from video footage captured by street cameras and flying drones, according to thousands of pages of internal documents that provide new details about the government’s ambitions to build out a powerful tool for advanced surveillance.
From DSC: This doesn’t surprise me. But it’s yet another example of opaqueness involving technology. And who knows to what levels our Department of Defense has taken things with AI, drones, and robotics.
A handful of companies control what PricewaterhouseCoopers called a “$15.7 trillion game changer of an industry.” Those companies employ or finance the work of a huge chunk of the academics who understand how to make LLMs. This leaves few people with the expertise and authority to say, “Wait, why are these companies blurring the distinction between what is human and what’s a language model? Is this what we want?”
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Bender knows she’s no match for a trillion-dollar game changer slouching to life. But she’s out there trying. Others are trying too. LLMs are tools made by specific people — people who stand to accumulate huge amounts of money and power, people enamored with the idea of the singularity. The project threatens to blow up what is human in a species sense. But it’s not about humility. It’s not about all of us. It’s not about becoming a humble creation among the world’s others. It’s about some of us — let’s be honest — becoming a superspecies. This is the darkness that awaits when we lose a firm boundary around the idea that humans, all of us, are equally worthy as is.
From DSC: I thought that the article made a good point when it asserted:
The pace of technological advancement is booming aggressively and conversations around ChatGPT snatching away jobs are becoming more and more frequent. The future of work is definitely going to change and that makes it clear that the approach toward education is also demanding a big shift.
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A report from Dell suggests that 85% of jobs that will be around in 2030 do not exist yet. The fact becomes important as it showcases that the jobs are not going to vanish, they will just change and most of the jobs by 2030 will be new.
Thus the question: What is the future of human agency? Pew Research Center and Elon University’s Imagining the Internet Center asked experts to share their insights on this; 540 technology innovators, developers, business and policy leaders, researchers, academics and activists responded. Specifically, they were asked:
By 2035, will smart machines, bots and systems powered by artificial intelligence be designed to allow humans to easily be in control of most tech-aided decision-making that is relevant to their lives?
The results of this nonscientific canvassing:
56% of these experts agreed with the statement that by 2035 smart machines, bots and systems will not be designed to allow humans to easily be in control of most tech-aided decision-making.
44% said they agreed with the statement that by 2035 smart machines, bots and systems will be designed to allow humans to easily be in control of most tech-aided decision-making.
What are the things humans really want agency over? When will they be comfortable turning to AI to help them make decisions? And under what circumstances will they be willing to outsource decisions altogether to digital systems?
The next big threat to AI might already be lurking on the web — from zdnet.com by Danny Palmer; via Sam DeBrule Artificial intelligence experts warn attacks against datasets used to train machine-learning tools are worryingly cheap and could have major consequences.
Excerpts:
Data poisoning occurs when attackers tamper with the training data used to create deep-learning models. This action means it’s possible to affect the decisions that the AI makes in a way that is hard to track.
By secretly altering the source information used to train machine-learning algorithms, data-poisoning attacks have the potential to be extremely powerful because the AI will be learning from incorrect data and could make ‘wrong’ decisions that have significant consequences.
Normally I would make the standard arguments against technologically-driven unemployment — see good summaries by Henry Hazlitt (chapter 7) and Frédéric Bastiat (his metaphor directly relevant to AI). And I will come back and make those arguments soon. But I don’t even think the standand arguments are needed, since another problem will block the progress of AI across most of the economy first.
Which is: AI is already illegal for most of the economy, and will be for virtually all of the economy.
How do I know that? Because technology is already illegal in most of the economy, and that is becoming steadily more true over time.
How do I know that? Because:
From DSC: And for me, it boils down to an inconvenient truth: What’s the state of our hearts and minds?
Have our hearts, our thinking, and/or our mindsets gone astray?
Do the products we create help or hurt others? It seems like too many times our perspective is, “We will sell whatever they will buy, regardless of its impact on others — as long as it makes us money and gives us the standard of living that we want.” Perhaps we could poll some former executives from Philip Morris on this topic.
Or we will develop this new technology because we can develop this new technology. Who gives a rat’s tail about the ramifications of it?
Here’s the list of sources: https://t.co/fJd4rh8kLy. The larger resource area at https://t.co/bN7CReGIEC has sample ChatGPT essays, strategies for mitigating harm, and questions for teachers to ask as well as a listserv.
— Anna Mills, amills@mastodon.oeru.org, she/her (@EnglishOER) January 11, 2023
Microsoft is reportedly eyeing a $10 billion investment in OpenAI, the startup that created the viral chatbot ChatGPT, and is planning to integrate it into Office products and Bing search.The tech giant has already invested at least $1 billion into OpenAI. Some of these features might be rolling out as early as March, according to The Information.
This is a big deal. If successful, it will bring powerful AI tools to the masses.So what would ChatGPT-powered Microsoft products look like? We asked Microsoft and OpenAI. Neither was willing to answer our questions on how they plan to integrate AI-powered products into Microsoft’s tools, even though work must be well underway to do so. However, we do know enough to make some informed, intelligent guesses. Hint: it’s probably good news if, like me, you find creating PowerPoint presentations and answering emails boring.
I have maintained for several years, including a book ‘AI for Learning’, that AI is the technology of the age and will change everything. This is unfolding as we speak but it is interesting to ask who the winners are likely to be.
People who have heard of GPT-3 / ChatGPT, and are vaguely following the advances in machine learning, large language models, and image generators. Also people who care about making the web a flourishing social and intellectual space.
That dark forest is about to expand. Large Language Models (LLMs) that can instantly generate coherent swaths of human-like text have just joined the party.
It is in this uncertain climate that Hassabis agrees to a rare interview, to issue a stark warning about his growing concerns. “I would advocate not moving fast and breaking things.”
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“When it comes to very powerful technologies—and obviously AI is going to be one of the most powerful ever—we need to be careful,” he says. “Not everybody is thinking about those things. It’s like experimentalists, many of whom don’t realize they’re holding dangerous material.” Worse still, Hassabis points out, we are the guinea pigs.
Demis Hassabis
Excerpt (emphasis DSC):
Hassabis says these efforts are just the beginning. He and his colleagues have been working toward a much grander ambition: creating artificial general intelligence, or AGI, by building machines that can think, learn, and be set to solve humanity’s toughest problems.Today’s AI is narrow, brittle, and often not very intelligent at all. But AGI, Hassabis believes, will be an “epoch-defining” technology—like the harnessing of electricity—that will change the very fabric of human life. If he’s right, it could earn him a place in history that would relegate the namesakes of his meeting rooms to mere footnotes.
But with AI’s promise also comes peril.In recent months, researchers building an AI system to design new drugs revealed that their tool could be easily repurposed to make deadly new chemicals. A separate AI model trained to spew out toxic hate speech went viral, exemplifying the risk to vulnerable communities online. And inside AI labs around the world, policy experts were grappling with near-term questions like what to do when an AI has the potential to be commandeered by rogue states to mount widespread hacking campaigns or infer state-level nuclear secrets.
Headteachers and university lecturers have expressed concerns that ChatGPT, which can provide convincing human-sounding answers to exam questions, could spark a wave of cheating in homework and exam coursework.
Now, the bot’s makers, San Francisco-based OpenAI, are trying to counter the risk by “watermarking” the bot’s output and making plagiarism easier to spot.
Students need now, more than ever, to understand how to navigate a world in which artificial intelligence is increasingly woven into everyday life. It’s a world that they, ultimately, will shape.
We hail from two professional fields that have an outsize interest in this debate. Joanne is a veteran journalist and editor deeply concerned about the potential for plagiarism and misinformation. Rebecca is a public health expert focused on artificial intelligence, who champions equitable adoption of new technologies.
We are also mother and daughter. Our dinner-table conversations have become a microcosm of the argument around ChatGPT, weighing its very real dangers against its equally real promise. Yet we both firmly believe that a blanket ban is a missed opportunity.
ChatGPT: Threat or Menace? — from insidehighered.com by Steven Mintz Are fears about generative AI warranted?
The rapid pace of change is driven by a “perfect storm” of factors, including the falling cost of computing power, the rise of data-driven decision-making, and the increasing availability of new technologies. “The speed of current breakthroughs has no historical precedent,”concluded Andrew Doxsey, co-founder of Libra Incentix, in an interview. “Unlike previous technological revolutions, the Fourth Industrial Revolution is evolving exponentially rather than linearly. Furthermore, it disrupts almost every industry worldwide.”
An updated version of the AI chatbot ChatGPT was recently released to the public.
I got the chatbot to write cover letters for real jobs and asked hiring managers what they thought.
The managers said they would’ve given me a call but that the letters lacked personality.
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I mentor a young lad with poor literacy skills who is starting a landscaping business. He struggles to communicate with clients in a professional manner.
I created a GPT3-powered Gmail account to which he sends a message. It responds with the text to send to the client. pic.twitter.com/nlFX9Yx6wR
From DSC:
Check out the items below. As with most technologies, there are likely going to be plusses & minuses regarding the use of AI in digital video, communications, arts, and music.
DC: What?!? Wow. I should have seen this coming. I can see positives & negatives here. Virtual meetings could become a bit more creative/fun. But apps could be a bit scarier in some instances, such as with #telelegal.
Professors, programmers and journalists could all be out of a job in just a few years, after the latest chatbot from the Elon Musk-founded OpenAI foundation stunned onlookers with its writing ability, proficiency at complex tasks, and ease of use.
The system, called ChatGPT, is the latest evolution of the GPT family of text-generating AIs. Two years ago, the team’s previous AI, GPT3, was able to generate an opinion piece for the Guardian, and ChatGPT has significant further capabilities.
In the days since it was released, academics have generated responses to exam queries that they say would result in full marks if submitted by an undergraduate, and programmers have used the tool to solve coding challenges in obscure programming languages in a matter of seconds – before writing limericks explaining the functionality.
Is the college essay dead? Are hordes of students going to use artificial intelligence to cheat on their writing assignments? Has machine learning reached the point where auto-generated text looks like what a typical first-year student might produce?
And what does it mean for professors if the answer to those questions is “yes”?
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Scholars of teaching, writing, and digital literacy say there’s no doubt that tools like ChatGPT will, in some shape or form, become part of everyday writing, the way calculators and computers have become integral to math and science. It is critical, they say, to begin conversations with students and colleagues about how to shape and harness these AI tools as an aide, rather than a substitute, for learning.
“Academia really has to look at itself in the mirror and decide what it’s going to be,” said Josh Eyler, director of the Center for Excellence in Teaching and Learning at the University of Mississippi, who has criticized the “moral panic” he has seen in response to ChatGPT. “Is it going to be more concerned with compliance and policing behaviors and trying to get out in front of cheating, without any evidence to support whether or not that’s actually going to happen? Or does it want to think about trust in students as its first reaction and building that trust into its response and its pedagogy?”
ChatGPT is incredibly limited, but good enough at some things to create a misleading impression of greatness.
it’s a mistake to be relying on it for anything important right now. it’s a preview of progress; we have lots of work to do on robustness and truthfulness.
1/Large language models like Galactica and ChatGPT can spout nonsense in a confident, authoritative tone. This overconfidence – which reflects the data they’re trained on – makes them more likely to mislead.
The thing is, a good toy has a huge advantage: People love to play with it, and the more they do, the quicker its designers can make it into something more. People are documenting their experiences with ChatGPT on Twitter, looking like giddy kids experimenting with something they’re not even sure they should be allowed to have. There’s humor, discovery and a game of figuring out the limitations of the system.
And on the legal side of things:
In the legal education context, I’ve been playing around with generating fact patterns and short documents to use in exercises.
I got lucky—my encounter was with a drone in virtual reality as part of an experiment by a team from University College London and the London School of Economics. They’re studying how people react when meeting police drones, and whether they come away feeling more or less trusting of the police.
It seems obvious that encounters with police drones might not be pleasant. But police departments are adopting these sorts of technologies without even trying to find out.
“Nobody is even asking the question: Is this technology going to do more harm than good?” says Aziz Huq, a law professor at the University of Chicago, who is not involved in the research.
You’ve likely been reading for the last few minutes my arguments for why AI is going to change education. You may agree with some points, disagree with others…
Only, those were not my words.
An AI has written every single word in this essay up until here.
The only thing I wrote myself was the first sentence: Artificial Intelligence is going to revolutionize education. The images too, everything was generated by AI.
Satellite Billboards Are a Dystopian Future We Don’t Need — from gizmodo.com by George Dvorsky; with thanks to Laura Goodrich for this resource Brightly lit ads in orbit are technologically and economically viable, say Russian scientists. But can we not?
South Korea plans to provide digital identities encrypted by blockchain with smartphones to citizens in 2024 to facilitate its economic development., Bloomberg reported Monday.
The South Korean government stated that with the expansion of the digital economy, the ID embedded in the smartphone is an indispensable emerging technology to support the development of data.
From DSC: Interesting to see blockchain show up in the first item above on healthcare and also on this item coming out of South Korea for digital identities.
The Bruce Willis Deepfake Is Everyone’s Problem — from wired.com by Will Bedingfield; with thanks to Stephen Downes for this resource There’s a fight brewing over how Hollywood stars can protect their identities. But it’s not just actors who should be paying attention.
Excerpts:
Yet the question of “who owns Bruce Willis,” as Levy put it, isn’t only a concern for the Hollywood star and his representatives. It concerns actors unions across the world, fighting against contracts that exploit their members’ naivety about AI. And, for some experts, it’s a question that implicates everyone, portending a wilder, dystopian future—one in which identities are bought, sold, and seized.
“This is relevant not just to AI contracts [for synthetic performances], but any contract involving rights to one’s likeness and voice,” says Danielle S. Van Lier, assistant general counsel, intellectual property and contracts at SAG-AFTRA. “We have been seeing contracts that now include ‘simulation rights’ to performers’ images, voices, and performances. These contract terms are buried deep in the boilerplate of performance agreements in traditional media.”
Cyber attackers have quickly caught onto QR codes as a social vulnerability and attacks using them as the vector are on the rise.
It’s clear we intuitively trust QR codes, even though this trust is poorly founded. To get a clearer picture of exactly how QR codes could present a threat, I did some digging. Through research, I discovered a variety of ways QR codes can be used maliciously, to steal not only personal information but provide a solid base of information from which to attack an organisation.
Image generators like Stable Diffusion can create what look like real photographs or hand-crafted illustrations depicting just about anything a person can imagine. This is possible thanks to algorithms that learn to associate the properties of a vast collection of images taken from the web and image databases with their associated text labels. Algorithms learn to render new images to match a text prompt in a process that involves adding and removing random noise to an image.
It’s hardly news to talk about the AI developments of the last month. DALL-E is increasingly popular, and being used in production. Google has built a robot that incorporates a large language model so that it can respond to verbal requests. And we’ve seen a plausible argument that natural language models can be made to reflect human values, without raising the question of consciousness or sentience.
For the first time in a long time we’re talking about the Internet of Things. We’ve got a lot of robots, and Chicago is attempting to make a “smart city” that doesn’t facilitate surveillance. We’re also seeing a lot in biology. Can we make a real neural network from cultured neurons? The big question for biologists is how long it will take for any of their research to make it out of the lab.
Companies have been increasingly complaining to the FBI about prospective employees using real-time deepfake video and deepfake audio for remote interviews, along with personally identifiable information (PII), to land jobs at American companies.
One place they’re likely getting the PII is through posting fake job openings, which enables them to harvest job candidate information, resumes and more, according to the FBI.
The main drivers appear to be money, espionage, access to company systems and unearned career advancement.
THE NEXT GENERATION
The way we commute has already started to change. With next generation transportation projects, public transportation is becoming more efficient by employing self-driving buses and trains and installing automatic card-ticketing systems.
From DSC: But we need to look out here. As we’ve seen before, not everything is so rosy with emerging technologies. See this next item for example:
Cruise’s Robot Car Outages Are Jamming Up San Francisco— from wired.com by Aarian Marshall In a series of incidents, the GM subsidiary lost contact with its autonomous vehicles, leaving them frozen in traffic and trapping human drivers.
“A letter sent anonymously by a Cruise employee to the California Public Utilities Commission that month alleged that the company loses contact with its driverless vehicles ‘with regularity,’ blocking traffic and potentially hindering emergency vehicles.”
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