Lifeboat Foundation

When Descartes said “I think therefore I am” he probably didn’t know that he was answering a security question. Using behavioral or physical characteristics to identify people, biometrics, has gotten a big boost in the EU. The Orwellian sounding HUMABIO (Human Monitoring and Authentication using Biodynamic Indicators and Behavioral Analysis) is a well funded research project that seeks to combine sensor technology with the latest in biometrics to find reliable and non-obtrusive ways to identify people quickly. One of their proposed methods: scanning your brain stem. That’s right, in addition to reading your retinas, looking at your finger prints, and monitoring your voice, the security systems of the future may be scanning your brain.

How could they actually read your brain? What kind of patterns would they use to authenticate your identity? Yeah, that haven’t quite figured that out yet. HUMABIO is still definitely in the “pre-commercial” and “proof of concept” phase. They do have a nice ethics manual to read, and they’ve actually written some “stories” that illustrate the uses of their various works in progress, but they haven’t produced a fieldable instrument yet. In fact, this aspect of the STREP (Specific Targeted Research Project) would hardly be remarkable if we didn’t know more about the available technology from other sources.

On the day of the ChatGPT-4o announcement, Sam Altman sat down to share behind-the-scenes details of the launch and offer his predictions for the future of AI. Altman delves into OpenAI’s vision, discusses the timeline for achieving AGI, and explores the societal impact of humanoid robots. He also expresses his excitement and concerns about AI personal assistants, highlights the biggest opportunities and risks in the AI landscape today, and much more.

(00:00) Intro.
(00:50) The Personal Impact of Leading OpenAI
(01:44) Unveiling Multimodal AI: A Leap in Technology.
(02:47) The Surprising Use Cases and Benefits of Multimodal AI
(03:23) Behind the Scenes: Making Multimodal AI Possible.
(08:36) Envisioning the Future of AI in Communication and Creativity.
(10:21) The Business of AI: Monetization, Open Source, and Future Directions.
(16:42) AI’s Role in Shaping Future Jobs and Experiences.
(20:29) Debunking AGI: A Continuous Journey Towards Advanced AI
(24:04) Exploring the Pace of Scientific and Technological Progress.
(24:18) The Importance of Interpretability in AI
(25:11) Navigating AI Ethics and Regulation.
(27:26) The Safety Paradigm in AI and Beyond.
(28:55) Personal Reflections and the Impact of AI on Society.
(29:11) The Future of AI: Fast Takeoff Scenarios and Societal Changes.
(30:59) Navigating Personal and Professional Challenges.
(40:21) The Role of AI in Creative and Personal Identity.
(43:09) Educational System Adaptations for the AI Era.
(44:30) Contemplating the Future with Advanced AI

Continue reading “Sam Altman talks GPT-4o and Predicts the Future of AI” »

Welcome to the era of ethical algorithms.

Feeling Bad About Feeling Good?

Summary: A new study explores the complex moral landscape of revenge, revealing that people’s reactions to revenge vary significantly based on the emotions displayed by the avenger. Conducted across four surveys involving Polish students and American adults, the study found that avengers who demonstrate satisfaction are viewed as more competent, whereas those expressing pleasure are seen as immoral.

These perceptions shift dramatically when individuals imagine themselves in the avenger’s shoes, tending to view their own actions as less moral compared to others. The findings challenge conventional views on revenge, suggesting that societal and personal perspectives on morality and competence deeply influence judgments of revengeful actions.

ChatGPT sparked a generative AI frenzy in the corporate workplace. Efforts to implement that technology responsibly, however, haven’t kept up.

This spring, the Hastings Center Report added a new series of essays named after the field its pieces aim to explore. Neuroscience and Society produces open access articles and opinion pieces that address the ethical, legal, and societal issues presented by emerging neuroscience. The series will run roughly twice a year and was funded by the Dana Foundation to foster dynamic, sustained conversation among neuroscience researchers, legal and ethics scholars, policymakers, and wider publics.

The first edition of the series focuses on the topic of research studies and what is owed to people who volunteer to participate in clinical trials to develop implantable brain devices, such as deep-brain stimulators and brain-computer interfaces.

Imagine you have lived with depression for most of your life. Despite trying numerous medications and therapies, such as electroconvulsive therapy, you have not been able to manage your symptoms effectively. Your depression keeps you from maintaining a job, interacting with your friends and family, and generally prevents you from flourishing as a person.

A recent study revealed that when individuals are given two solutions to a moral dilemma, the majority tend to prefer the answer provided by artificial intelligence (AI) over that given by another human.

The recent study, which was conducted by Eyal Aharoni, an associate professor in Georgia State’s Psychology Department, was inspired by the explosion of ChatGPT and similar AI large language models (LLMs) which came onto the scene last March.

“I was already interested in moral decision-making in the legal system, but I wondered if ChatGPT and other LLMs could have something to say about that,” Aharoni said. “People will interact with these tools in ways that have moral implications, like the environmental implications of asking for a list of recommendations for a new car. Some lawyers have already begun consulting these technologies for their cases, for better or for worse. So, if we want to use these tools, we should understand how they operate, their limitations, and that they’re not necessarily operating in the way we think when we’re interacting with them.”

A new study has found that when people are presented with two answers to an ethical question, most will think the answer from artificial intelligence (AI) is better than the response from another person.

Summary: People often view AI-generated answers to ethical questions as superior to those from humans. In the study, participants rated responses from AI and humans without knowing the source, and overwhelmingly favored the AI’s responses in terms of virtuousness, intelligence, and trustworthiness.

This modified moral Turing test, inspired by ChatGPT and similar technologies, indicates that AI might convincingly pass a moral Turing test by exhibiting complex moral reasoning. The findings highlight the growing influence of AI in decision-making processes and the potential implications for societal trust in technology.