71 Artificial Intelligence Examples to Know for 2024
Super Artificial General Intelligence (Super-AGI)
Source: Image by Luke Olson / OpenArt ai 2024
We've all heard about artificial intelligence (AI), perhaps the biggest technical revolution since the internet. AI will impact the economy (jobs), healthcare, and people's daily lives. Since robots and AI are already here making a difference, what is the next big step for technology? We are about to observe an exponential advance in AI because as we soon enable AIs to program themselves, a super-intelligent entity will emerge.
Artificial general intelligence (AGI) is the field of AI research attempting to create software with human-like intelligence. Even newer is the idea that future AGI systems will begin programming themselves: coding, self-prompting, and data mining their own machine learning algorithms to create ever more intelligent AGI. Ultimately, the AGIs will grow themselves into "super intelligent" AGI models that will be smarter than humans. Wow.
Normal human intelligence will seem relatively elementary when compared to these future super-AGI machines. What is worrying is the possibility that the future super-AGIs will become self-aware and conscious. Will these sentient digital entities decide to protect their own existence at the expense of their human creators? Before that happens, consider whether it's too late to install needed safety rules and guardrails: The question for AGI developers is whether we are now facing an "Oppenheimer moment" where decisions about building super-AGI today will determine humanity's future.
In Situational Awareness, author Leopold Aschenbrenner makes several predictions. One essential idea is that AGI models will be built to teach and program themselves, with machine learning algorithms orchestrated by the AGIs themselves. "We don't need to automate everything—just AI research. By 2025/26, machines will outpace many college graduates. By the end of the decade, they ('super-AGIs') will be smarter than you or I."
In just a few years, super-AGI models will expand their problem-solving and reasoning capacity exponentially to ultimately produce qualitative leaps in intelligence that are orders of magnitude (OOM) beyond what we think of as normal human intelligence today. Those virtual assistants we interact with online today will soon be like extinct dinosaurs compared to the realism of future "virtual agents" who will function more like coworkers than today's chatbots. As super-AGI systems self-evolve, they'll engineer themselves to increase their intelligence through OOMs in each successive version. As we instill the ability to self-teach, AGI machines will reach "superintelligence" beyond that of their human creators by about 2028.
Many see the vast potential of intelligent machines. But there are gloomy prognosticators who foretell that super-AGI poses an existential threat to humanity itself. Which of the two views, utopian or dystopian, is correct? We do not know, and therefore, preparation and caution are advisable. A recent paper in Science addresses the kinds of safeguards AI researchers should consider now. (1)
Despite the cautionary warnings for engineers and AI developers, what is clear is that this technology is approaching, and mental health professionals must acknowledge super-AGI's practical implications for psychology. A virtual revolution in AI-assisted virtual health care—and especially in mental health—is ongoing, and AI already impacts mental healthcare delivery in many ways. (2)
One scenario will create a future AGI-driven mental health virtual practitioner who can:
Just as autonomous driving AIs learn from the behavior of millions of driver-miles, so too will future super-AGI therapists be trained and informed by worldwide scientific theory and data and potentially infinite learning from observations of human-delivered therapy. Even better, since it's an AGI, this expert personal mental healthcare provider will be instantly available to anyone, on-call 24/7, essentially for free. In this way, super-AGI therapists may help improve mental health delivery for the social good.
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These advances will happen so long as we can anticipate and prevent ethical problems. Humans are imperfect, and thus, our creations may reflect our biases or mirror our worst instincts. Given the anticipated explosive rate of growth, we should continue to develop AGI, as we would with any new clinical device, to ensure safety while carefully weighing the risks and benefits to humanity.
What Is Artificial General Intelligence, And Is It A Useful Concept?
Artificial General Intelligence (AGI) has long been a topic of fascination and debate among researchers, technologists, and philosophers. Unlike narrow AI, which is designed to perform specific tasks, AGI aims to replicate human-like intelligence and versatility. This article delves into what Artificial General Intelligence is, its potential applications, challenges, and whether it is a useful concept in the advancement of artificial intelligence.
Defining Artificial General IntelligenceArtificial General Intelligence refers to a type of AI that possesses the ability to understand, learn, and apply knowledge across a wide range of tasks, similar to the cognitive capabilities of humans. While narrow AI systems are tailored to perform specific functions—like recognizing speech, playing chess, or driving a car—AGI would be capable of performing any intellectual task that a human being can do. This includes reasoning, problem-solving, understanding natural language, and adapting to new situations without needing to be specifically programmed for each task.
Potential Applications of AGI1. Healthcare: AGI could revolutionize healthcare by diagnosing diseases, developing treatment plans, and even performing surgeries with precision. Its ability to process vast amounts of medical data and learn from it could lead to breakthroughs in personalized medicine and predictive analytics.
2. Education: In education, AGI could serve as an advanced tutor, capable of teaching and mentoring students individually based on their learning styles and progress. It could also assist in curriculum development and educational research.
3. Research and Development: AGI could accelerate scientific research by analyzing complex data sets, generating hypotheses, and even conducting experiments. Its capacity to work across various scientific disciplines could lead to innovative discoveries.
4. Business and Finance: AGI could transform business operations by optimizing processes, predicting market trends, and improving decision-making. In finance, it could enhance risk management, fraud detection, and investment strategies.
Challenges in Developing AGI1. Technical Complexity: Creating AGI involves significant technical challenges, including developing algorithms that can mimic human cognitive processes. Current AI systems are far from achieving the generality and flexibility required for AGI.
2. Computational Resources: AGI would require immense computational power and data. The infrastructure needed to support such a system is currently beyond our reach, posing a significant barrier to its development.
3. Ethical Concerns: The development of AGI raises profound ethical questions. Concerns about job displacement, privacy, decision-making autonomy, and the potential misuse of AGI are significant. Ensuring that AGI aligns with human values and societal norms is a critical challenge.
4. Safety and Control: Ensuring the safety of AGI is paramount. An AGI system could potentially surpass human intelligence, leading to scenarios where it might act in ways that are unpredictable or harmful. Developing robust control mechanisms is essential to prevent unintended consequences.
Is AGI a Useful Concept?The usefulness of AGI as a concept can be examined from several perspectives:
1. Research Motivation: AGI serves as a north star for AI research. It motivates researchers to push the boundaries of what is possible in artificial intelligence. By striving for AGI, we develop more advanced and capable narrow AI systems along the way.
2. Holistic Problem-Solving: Unlike narrow AI, which excels in specific domains, AGI's potential to address complex, multifaceted problems makes it a valuable concept. For example, tackling global issues like climate change, poverty, and disease might benefit from AGI's ability to integrate knowledge and strategies across disciplines.
3. Ethical Frameworks: The pursuit of AGI encourages the development of ethical frameworks and safety protocols that are crucial for the responsible advancement of AI technology. By anticipating the challenges AGI might bring, we can better prepare for and mitigate potential risks.
4. Philosophical Inquiry: AGI stimulates important philosophical discussions about the nature of intelligence, consciousness, and what it means to be human. These inquiries can deepen our understanding of ourselves and our place in the universe.
ConclusionArtificial General Intelligence represents a bold and ambitious frontier in the field of artificial intelligence. While the journey toward achieving AGI is fraught with technical, ethical, and philosophical challenges, the concept remains a powerful catalyst for innovation and exploration. Whether AGI will ultimately be realized remains to be seen, but its pursuit undeniably drives progress and inspires a deeper investigation into the nature of intelligence and the future of human-technology interaction.
See Also: Difference Between Artificial Intelligence and Machine Learning
Opinion: The Risks Of AI Could Be Catastrophic. We Should Empower Company Workers To Warn Us
Editor's Note: Lawrence Lessig is the Roy L. Furman Professor of Law and Leadership at Harvard Law School and the author of the book "They Don't Represent Us: Reclaiming Our Democracy." The views expressed in this commentary are his own. Read more opinion at CNN.
CNN —
In April, Daniel Kokotajlo resigned his position as a researcher at OpenAI, the company behind Chat GPT. He wrote in a statement that he disagreed with the way it is handling issues related to security as it continues to develop the revolutionary but still not fully understood technology of artificial intelligence.
On his profile page on the online forum "LessWrong," Kokotajlo — who had worked in policy and governance research at Open AI — expanded on those thoughts, writing that he quit his job after "losing confidence that it would behave responsibly" in safeguarding against the potentially dire risks associated with AI.
And in a statement issued around the time of his resignation, he blamed the culture of the company for forging ahead without heeding the warning about the dangers it might be unleashing.
"They and others have bought into the 'move fast and break things' approach and that is the opposite of what is needed for technology this powerful and this poorly understood," Kokotajlo wrote.
OpenAI pressed him to sign an agreement promising not to disparage the company, telling him that if he refused, he would lose his vested equity in the company. The New York Times has reported that equity was worth $1.7 million. Nevertheless, he declined, apparently choosing to reserve his right to publicly voice his concerns about AI.
When news broke about Kokotajlo's departure from OpenAI and the alleged pressure from the company to get him to sign a non-disclosure agreement, the company's CEO Sam Altman quickly apologized.
"This is on me," Altman wrote on X, (formerly known as Twitter), "and one of the few times I've been genuinely embarrassed running openai; I did not know this was happening and I should have." What Altman didn't reveal is how many other company employees/executives might have been forced to sign similar agreements in the past. In fact, for many years and according to former employees, the company has threatened to cancel employees' vested equity if they didn't promise to play nice.
Altman's apology was effective, however, in tamping down attention to OpenAI's legal blunder of requiring these agreements. The company was eager to move on and most in the press were happy to oblige. Few news outlets reported the obvious legal truth that such agreements were plainly illegal under California law. Employees had for years thought themselves silenced by the promise they felt compelled to sign, but a self-effacing apology by a CEO was enough for the media, and the general public, to move along.
We should pause to consider just what it means when someone is willing to give up perhaps millions of dollars to preserve the freedom to speak. What, exactly, does he have to say? And not just Kokotajlo, but the many other OpenAI employees who have recently resigned, many now pointing to serious concerns about the dangers inherent in the company's technology.
I knew Kokotajlo and reached out to him after he quit; I'm now representing him and 10 other current and former OpenAI employees on a pro bono basis. But the facts I relate here come only from public sources.
Many people refer to concerns about the technology as a question of "AI safety." That's a terrible term to describe the risks that many people in the field are deeply concerned about. Some of the leading AI researchers, including Turing Prize winner Yoshua Bengio and Sir Geoffrey Hinton, the computer expert and neuroscientist sometimes referred to as "the godfather of AI," fear the possibility of runaway systems creating not just "safety risks," but catastrophic harm.
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And while the average person can't imagine how anyone could lose control of a computer ("just unplug the damn thing!"), we should also recognize that we don't actually understand the systems that these experts fear.
Companies operating in the field of AGI — artificial general intelligence, which broadly speaking refers to the theoretical AI research attempting to create software with human-like intelligence, including the ability to perform tasks that it is not trained or developed for — are among the least regulated, inherently dangerous companies in America today. There is no agency that has legal authority to monitor how the companies develop their technology or the precautions they are taking.
Instead, we rely upon the good judgment of these corporations to ensure that risks are adequately policed. Thus, as a handful of companies race to achieve AGI, the most important technology of the century, we are trusting them and their boards to keep the public's interest first. What could possibly go wrong?
This oversight gap has now led a number of current and former employees at OpenAI to formally ask the companies to pledge to encourage an environment in which employees are free to criticize the company's safety precautions.
Their "Right to Warn" pledge asks companies:
First, to commit to revoking any "non-disparagement" agreement. (OpenAI has already promised to do as much; reports are that other companies may have similar language in their agreements that they've not yet acknowledged.)
Second, it asks companies to pledge to create an anonymous mechanism to give employees and former employees a way to raise safety concerns to the board, to regulators and to an independent AI safety organization.
Third, it asks companies to support a "culture of open criticism," to encourage employees and former employees to speak about safety concerns so long as they protect the corporation's intellectual property.
Finally — perhaps most interestingly — it asks companies to promise not to retaliate against employees who share confidential information when raising risk-related concerns, but pledges that employees would first channel their concerns through a confidential and anonymous process — if, and when, the company creates it. This is designed to create the incentive to build a mechanism to protect confidential information while enabling warnings.
Get our free weekly newsletterSuch a "Right to Warn" would be unique in the regulation of American corporations. It is justified by the absence of effective regulation, a condition that could well change if Congress got around to addressing the risks that so many have described. And it is necessary because ordinary whistleblower protections don't cover conduct that is not itself regulated.
The law — especially California law — would give employees a wide berth to report illegal activities; but when little is regulated, little is illegal. Thus, so long as there is no effective regulation of these companies, it is only the employees who can identify the risks that the company is ignoring.
Even if the AI companies endorsed a "Right to Warn," no one should imagine that it would be easy for any current or former employee to call out an AI company. Whistleblowers are not favorite co-workers, even if they are respected by some. And even with formal protections, the choice to speak out inevitably has consequences for their future employment opportunities — and friendships.
Obviously, it is not fair that we rely upon self-sacrifice to ensure that private corporations are not putting profit above catastrophic risks. This is the job of regulation. But if these former employees are willing to lose millions for the freedom to say what they know, maybe it is time that our representatives built the structures of oversight that would make such sacrifices unnecessary.
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