Toggle light / dark theme

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.”

“There is still a great deal of stigma around the use of substances during pregnancy,” said Dr. Jamie Lo, M.D., M.C.R. “Our hope is that this research supports more open and productive conversations that ultimately result in a healthier pregnancy.”


It has long been known that smoking during pregnancy can result in bad health for newborns, but what are the consequences of smoking both nicotine and cannabis during pregnancy? This is what a recent study published in JAMA hopes to address as a team of researchers investigated the potential health risks for newborns when pregnant mothers smoke both nicotine and cannabis during pregnancy. This study holds the potential to help researchers, medical practitioners, and the public better understand the health risks of cannabis as its recreational use continues to become legalized across the United States.

“With the growing legalization of cannabis around the country, there is often a perception that cannabis is safe in pregnancy,” said Dr. Jamie Lo, M.D., M.C.R., who is an associate professor of obstetrics and gynecology at the Oregon Health & Science University School of Medicine and a co-author on the study. “Because we know that many people who use cannabis often use tobacco or nicotine products, we wanted to better understand the potential health implications on both the pregnant individual and the infant.

For the study, the researchers analyzed hospital discharge data of 3,129,259 pregnant women whose records were obtained from the California Department of Public Health and the California Department of Health Care Access and Information with the goal of using specific health codes to ascertain cannabis and nicotine use during pregnancy, and specifically the health outcomes of their newborns resulting from this exposure. In the end, the researchers determined that 23,007 used cannabis during pregnancy, 56,811 used nicotine during pregnancy, and 10,312 used both during pregnancy.

The OpenAI Startup Fund, a venture fund related to — but technically separate from — OpenAI that invests in early-stage, typically AI-related companies across education, law and the sciences, has quietly closed a $15 million tranche.

According to a filing with the U.S. Securities and Exchange Commission, two unnamed investors contributed the $15 million in new cash on or around April 19. The paperwork was submitted on April 25, and mentions Ian Hathaway, the OpenAI Startup Fund’s manager and sole partner.

The capital was transferred to a legal entity called a special purpose vehicle, or SPV, associated with the OpenAI Startup Fund: OpenAI Startup Fund SPV II, L.P.

Fascinating vision/plan by the one and only Sam Altman of how to update our economic systems to benefit everyone in the context of rapidly accelerating technological change.


My work at OpenAI reminds me every day about the magnitude of the socioeconomic change that is coming sooner than most people believe. Software that can think and learn will do more and more of the work that people now do. Even more power will shift from labor to capital. If public policy doesn’t adapt accordingly, most people will end up worse off than they are today.

We need to design a system that embraces this technological future and taxes the assets that will make up most of the value in that world–companies and land–in order to fairly distribute some of the coming wealth. Doing so can make the society of the future much less divisive and enable everyone to participate in its gains.

In the next five years, computer programs that can think will read legal documents and give medical advice. In the next decade, they will do assembly-line work and maybe even become companions. And in the decades after that, they will do almost everything, including making new scientific discoveries that will expand our concept of “everything.”

A theory of consciousness should capture its phenomenology, characterize its ontological status and extent, explain its causal structure and genesis, and describe its function. Here, I advance the notion that consciousness is best understood as an operator, in the sense of a physically implemented transition function that is acting on a representational substrate and controls its temporal evolution, and as such has no identity as an object or thing, but (like software running on a digital computer) it can be characterized as a law. Starting from the observation that biological information processing in multicellular substrates is based on self organization, I explore the conjecture that the functionality of consciousness represents the simplest algorithm that is discoverable by such substrates, and can impose function approximation via increasing representational coherence. I describe some properties of this operator, both with the goal of recovering the phenomenology of consciousness, and to get closer to a specification that would allow recreating it in computational simulations.