Considerable advancements have been made in various NLP tasks based on the impressive power of large language models (LLMs) and many NLP applications are deployed in our daily lives. In this work, we challenge the capability of LLMs with the new task of Ethical Quandary Generative Question Answering. Ethical quandary questions are more challenging to address because multiple conflicting answers may exist to a single quandary. We explore the current capability of LLMs in providing an answer with a deliberative exchange of different perspectives to an ethical quandary, in the approach of Socratic philosophy, instead of providing a closed answer like an oracle. We propose a model that searches for different ethical principles applicable to the ethical quandary and generates an answer conditioned on the chosen principles through prompt-based few-shot learning. We also discuss the remaining challenges and ethical issues involved in this task and suggest the direction toward developing responsible NLP systems by incorporating human values explicitly.

With 2021 behind us, we're going down memory lane to highlight biotech innovations that shaped the year--with impact that will likely reverberate for many years to come. Covid-19 dominated the news, but science didn't stand still. CRISPR spun off variations with breathtaking speed, expanding into a hefty toolbox packed with powerhouse gene editors far more efficient, reliable, and safer than their predecessors. CRISPRoff, for example, hijacks epigenetic processes to reversibly turn genes on and off--all without actually snipping or damaging the gene itself. Prime editing, the nip-tuck of DNA editing that only snips--rather than fully cutting--DNA received an upgrade to precisely edit up to 10,000 DNA letters in a variety of cells.

AI was deployed across multiple areas in health during the pandemic, from analysing the sound of a patient's cough to predicting mortality. More than 4,000 scientific papers have been published on AI and COVID-19 since the pandemic began, Alessandro Blasimme, a senior scientist in the Health Policy Lab at the Swiss Federal Institute of Technology in Zurich, told participants at a recent panel on the future of science and technology in Europe. The ethical quandaries posed by AI in healthcare range from opaque decision-making to biases against certain social groups that get embedded in a technology. For instance, if an algorithm drew on the fact that older people were more likely to die from COVID, it could introduce age-based bias to decisions. And, while the public have accepted border restrictions, "what people might not be used to is, the idea that there is a system that does this screening in the background – something that is not visible, it's not transparent."

Corporal punishment, wearing fur, pineapple on pizza – moral dilemmas, are by their very nature, hard to solve. That's why the same ethical questions are constantly resurfaced in TV, films and literature. But what if AI could take away the brain work and answer ethical quandaries for us? Ask Delphi is a bot that's been fed more than 1.7m examples of people's ethical judgments on everyday questions and scenarios. If you pose an ethical quandary, it will tell you whether something is right, wrong, or indefensible. Users just put a question to the bot on its website, and see what it comes up with.

Corporal punishment, wearing fur, pineapple on pizza – moral dilemmas, are by their very nature, hard to solve. That's why the same ethical questions are constantly resurfaced in TV, films and literature. But what if AI could take away the brain work and answer ethical quandaries for us? Ask Delphi is a bot that's been fed more than 1.7m examples of people's ethical judgments on everyday questions and scenarios. If you pose an ethical quandary, it will tell you whether something is right, wrong, or indefensible. Users just put a question to the bot on its website, and see what it comes up with.

Nowhere could the application of machine learning prove more important -- nor more risky -- than in law enforcement and national security. In this article, I'll review this area and then cover six perplexing and pressing ethical quandaries that arise. Predictive policing introduces a scientific element to law enforcement decisions, such as whether to investigate or detain, how long to sentence, and whether to parole. In making such decisions, judges and officers take into consideration the probability a suspect or defendant will be convicted for a crime in the future -- which is commonly the dependent variable for a predictive policing model. These independent variables may include prior convictions, income level, employment status, family background, neighborhood, education level, and the behavior of family and friends.

A lot of discussion and ethical thought about self-driving cars have focused on tragic dilemmas, like hypotheticals in which a car has to decide whether to run over a group of schoolchildren or plunge off a cliff, killing its own occupants. But those sorts of situations are extreme cases. As the most recent crash – in which a self-driving car killed a pedestrian in Tempe, Arizona – demonstrates, the mundane, everyday situations at every pedestrian crossing, turn and intersection present much harder and broader ethical quandaries. As a philosopher working with engineers in Stanford's Centre for Automotive Research, I was initially surprised that we spent our lab meetings discussing what I thought was an easy question: how should a self-driving car approach a pedestrian crossing? My assumption had been that we would think about how a car should decide between the lives of its passengers and the lives of pedestrians.

A lot of discussion and ethical thought about self-driving cars have focused on tragic dilemmas, like hypotheticals in which a car has to decide whether to run over a group of schoolchildren or plunge off a cliff, killing its own occupants. But those sorts of situations are extreme cases. As the most recent crash – in which a self-driving car killed a pedestrianin Tempe, Arizona – demonstrates, the mundane, everyday situations at every crosswalk, turn and intersection present much harder and broader ethical quandaries. As a philosopher working with engineers in Stanford's Center for Automotive Research, I was initially surprised that we spent our lab meetings discussing what I thought was an easy question: How should a self-driving car approach a crosswalk? My assumption had been that we would think about how a car should decide between the lives of its passengers and the lives of pedestrians.

Remember that one rider is wearing a helmet, whereas the other is not. As a matter of probability, the rider with the helmet has a greater chance of survival if your car hits her. But here we can see that crash optimization isn't only about probabilistic harm reduction. For example, it seems unfair to penalize motorcyclists who wear helmets by programming cars to strike them over non-helmet wearers, particularly in cases where helmet use is a matter of law. Furthermore, it is good public policy to encourage helmet use; they reduce fatalities by 22-42 percent, according to a National Highway Traffic Safety Administration report. As a motorcyclist myself, I may decide not to wear a helmet if I know that crash-optimization algorithms are programmed to hit me when wearing my helmet.