Scientists and tech industry leaders, including high-level executives at Microsoft and Google, issued a new warning Tuesday about the perils that artificial intelligence poses to humankind. "Mitigating the risk of extinction from AI should be a global priority alongside other societal-scale risks such as pandemics and nuclear war," the statement said. Sam Altman, CEO of ChatGPT maker OpenAI, and Geoffrey Hinton, a computer scientist known as the godfather of artificial intelligence, were among the hundreds of leading figures who signed the statement, which was posted on the Center for AI Safety's website. Worries about artificial intelligence systems outsmarting humans and running wild have intensified with the rise of a new generation of highly capable AI chatbots such as ChatGPT. It has sent countries around the world scrambling to come up with regulations for the developing technology, with the European Union blazing the trail with its AI Act expected to be approved later this year.

These 7 tools can generate emails, transcribe interviews, improve your writing, create daily work schedules, and more.

If you believe all the doom and gloom in the news today, you might think automation and the deployment of AI-enabled systems at work will replace scores of jobs worldwide. Is AI Really a Job Killer? But management and technology experts Thomas Davenport and Steven Miller argue that AI is not a job destroyer -- no matter what other predictions might say. Yes, AI and intelligent technology will take over some jobs, but that will free up workers to do more challenging and important work. Tom and Steven recently completed a book on this topic called Working with AI: Real Stories of Human-Machine Collaboration, and I got the chance to speak with them about their predictions for how AI will fit in with the workplaces of the future.

We are well aware that Google's Artificial Intelligence is one of the most advanced technologies in this field. In other words, it is not surprising that Google is capable of developing an Artificial Intelligence that understands how the human brain operates and can imitate its capabilities… Those of us who are customers of this company have been impressed on multiple occasions by their ability to know each other too well and to anticipate our every move. Blake Lemoine, a Google engineer, expressed surprise at the possibility of Google's technology knowing us and imitating our behavior based on predictions about our preferences. It all began when Blake Lemoine was working on the advancements of LaMDA (Language Model for Dialogue Applications), a Google Artificial Intelligence designed to have conversations and eventually perfect Google searches by analyzing sentences and patterns in conversation, one of the many ways that artificial intelligences operate and learn. This project's primary objective is to ensure that the responses of Google's Artificial Intelligence in conversations transcend the automatic responses that characterize bots, for instance, and that different topics can be covered and a dialogue can progress naturally.

The Internet of the future could be written by bots, but will that make it better or worse? Experts at the Copenhagen Institute for Future Studies (CIFS) are raising questions about AI-generated content, and how it could come to dominate the metaverse and other digital locations. CIFS expert Timothy Shoup estimates that 99 percent to 99.9 percent of the internet's content will be AI-generated by 2025 to 2030, especially if models like OpenAI's GPT-3 achieve wider adoption. "The internet would be completely unrecognizable," Shoup told colleague Sofie Hvitved. As its capabilities advance, the idea is that AI could start to generate entire online worlds, along with all the stuff that inhabits them -- not to mention all the online material that's currently mostly made by humans.

The frequency and magnitude of natural disasters such as hurricanes, wildfires and floods has been growing for a number of years. Panelists for the Advanced Technology Academic Research Center's Jan. 26 webinar "Leveraging Predictive Analytics to Address Climate Change Issues" discussed how the use of artificial intelligence and machine learning can provide both short- and long-term guidance for decisionmakers considering how to ameliorate impacts. According to the National Centers for Environmental Information, which is part of the National Oceanic and Atmospheric Administration, in 2021 there were 20 weather and climate disaster events that incurred losses of more than $1 billion each. From 1980 to 2021, the annual average was 7.4 events (adjusted for inflation), but from 2017 to 2021, the most recent five years, the average number of events was 17.2 (adjusted for inflation). In short, the problem is getting worse, and faster.

A "lethal" weaponized drone "hunted down" and "remotely engaged" human targets without its handlers' say-so during a conflict in Libya last year, according to a United Nations report first covered by New Scientist this week. Whether there were any casualties remains unclear, but if confirmed, it would likely be the first recorded death carried out by an autonomous killer robot. In March 2020, a Kargu-2 attack quadcopter, which the agency called a "lethal autonomous weapon system," targeted retreating soldiers and convoys led by Libyan National Army's Khalifa Haftar during a civil conflict with Libyan government forces. "The lethal autonomous weapons systems were programmed to attack targets without requiring data connectivity between the operator and the munition: in effect, a true'fire, forget and find' capability," the UN Security Council's Panel of Experts on Libya wrote in the report. It remains unconfirmed whether any soldiers were killed in the attack, although the UN experts imply as much.

Artificial intelligence and machine learning are two expanding means logistics companies can use to gather and process tremendous amounts of data …

Is Python the best language for machine learning? Do you foresee any major changes to the popular ML software stack? In ML, 90% of the ideas you try fail, so iteration speed is critical. Python allows you to iterate faster (in ML) than any other language. I see many changes to the ML software stack, particularly on the infrastructure side, and possibly on the framework side as well (keep an eye on Jax), but I don't see Python being dethroned anytime soon.

Most of us want digital privacy, and most of us also want autocorrection that works, speech to text that is accurate, and smart systems that find all our selfies with Serena, or surface the most important emails we need right now. But are those two imperatives in direct opposition? According to some tech analysts and AI experts, they are. Especially those who are experiencing huge issues with iPhone's autocorrection capability in Apple's latest mobile operating system upgrade, iOS 13. "It's way worse on my iPhone," says veteran industry observer Robert Scoble, chief strategy officer at Infinite Retina. "And I've tried several things to fix it, including deleting all the settings and deleting all the history and trying to reboot everything ... I'm seeing a lot of bugs in the spellchecker where it's putting capitalization where it doesn't need to go, where it's switching words a lot more often than it used to. Apple's iOS 13's spellcheck was so bad Scoble ran a Twitter poll, asking his 400,000 followers whether they had similar issues. Twitter polls are hardly scientific, of course. But there's a broad range of people who are claiming that Apple's recent software release has been a big backward step in terms of autocorrection. "iOS 13 got significantly worse for me," says mobile entrepreneur Albert Renshaw, CEO at Apps4Life. "I've been learning French with Duolingo and have been typing in French every day for a little over a year in that app, but have never had an issue with it affecting my autocorrect.