Apparently, one of generative AI’s extraordinary capabilities is unifying politicians, the public, and the private sector in regulating it.
We saw that today in a Senate Judiciary Committee hearing(opens in a new tab) about how to govern AI. OpenAI CEO Sam Altman, IBM chief privacy and trust officer Christina Montgomery, and NYU emeritus professor Gary Marcus testified in front of the privacy, technology, and law subcommittee about what to do now that generative AI has been freed from Pandora’s Box. Altman was open and cooperative, even advocating for regulation of ChatGPT and generative AI. But that seemed to have a disarming effect on the subcommittee, who asked mostly softball questions.
Unfortunately, it turns out we actually kind of like watching Instagram Reels.
When Instagram first launched Reels and promised to pivot the social media platform to video, users were livid. We threw fits. Kylie Jenner demanded that we “make Instagram Instagram again.” And, at first, Reels flopped as a lame version of TikTok.
But, at Meta’s earnings call on Wednesday, Mark Zuckerberg reported that time spent on Instagram had risen by 24 percent, an engagement increase he blames on Instagram Reels.
Snapchat’s AI chatbot is now opening up to a global audience, the company announced today at its Snap Partner Summit. Initially launched in February, the feature originally allowed Snapchat’s paid subscribers to chat with an AI chatbot powered by OpenAI’s GPT technology directly in its app. Now it will be available for free. To date, users have sent nearly 2 million messages per day using the chatbot, Snap noted. With today’s global expansion, the feature is also being upgraded with new functionality, including the ability to add My AI to group chats, get recommendations for places on Snap Map and Lenses, and share Snaps with My AI and receive chat replies.
Leadership is a dynamic and constantly evolving field. As the world changes, so do the challenges that leaders face.
Throughout 2023, leaders will face new and unique challenges that will require them to adapt and innovate. In this article, I will outline five of these challenges and suggest practical steps that leaders can take to address them.
GETTING A CENSUS count wrong can cost communities big. A March 10 report from the US Census Bureau showed an overcount of white and Asian people and an undercount of people who identify as Black, Hispanic or Latino, or multiracial in 2020, a failure that has led to renewed calls to modernize the census.
Progress reaching historically undercounted groups has been slow, and the stakes are high. The once-a-decade endeavor informs the distribution of federal tax dollars and apportions members of the House of Representatives for each state, potentially redrawing the political map. According to emails obtained through a records request, Trump administration officials interfered in the population count to produce outcomes beneficial to Republicans, but problems with the census go back much further.
In February 2010, The Economist published a report called “Data, data everywhere.” Little did we know then just how simple the data landscape actually was. That is, comparatively speaking, when you consider the data realities we’re facing as we look to 2022.
In that Economist report, I spoke about society entering an “Industrial Revolution of Data,” which kicked off with the excitement around Big Data and continues into our current era of data-driven AI. Many in the field expected this revolution to bring standardization, with more signal and less noise. Instead, we have more noise, but a more powerful signal. That is to say, we have harder data problems with bigger potential business outcomes.
And, we’ve also seen big advances in artificial intelligence. What does that mean for our data world now? Let’s take a look back at where we were.
INSIDE AN ORDINARY-LOOKING home, a robot suspended from the ceiling slowly expands arms holding a sponge, before carefully wiping a kitchen surface clean. Nearby, another robot gently cleans a flat-screen television, causing it to wobble slightly.
The cleaning robots live inside a mock home located at the Toyota Research Institute in Los Altos, California. The institute’s researchers are testing a range of robot technologies designed to help finally realize the dream of a home robot.
After looking at homes in Japan, which were often small and cluttered, the researchers realized they needed a creative solution. “We thought, you know, how can we use the ceiling?” says Max Bajracharya, VP of Robotics at TRI.
In a world where technology is changing rapidly, it can be hard for businesses to keep up with shifting consumer demands. Take how customers interact with businesses, for instance. According to a recent study by Drift, people now prefer real-time interaction as they make their purchases, meaning that just having an online storefront is no longer enough.
For startups looking to grow a loyal customer base, the immediate needs of users can be especially intimidating and even seem, at times, insurmountable. Entrepreneurs with small employee bases would have no way of being there for every customer and anticipating each person’s needs in real time.
Artificial intelligence is allowing us all to consider surprising new ways to simplify the lives of our customers. As a product developer, your central focus is always on the customer. But new problems can arise when the specific solution under development helps one customer while alienating others.
We tend to think of AI as an incredible dream assistant to our lives and business operations, when that’s not always the case. Designers of new AI services should consider in what ways and for whom might these services be annoying, burdensome or problematic, and whether it involves the direct customer or others who are intertwined with the customer. When we apply AI services to make tasks easier for our customers that end up making things more difficult for others, that outcome can ultimately cause real harm to our brand perception.
If you’re training to be a concert violinist, you don’t want your technique to be merely “good enough.” A new computer system may soon be able to help, as it uses artificial intelligence (AI) to identify a user’s bow technique, and could perhaps even tell them how to improve their performance.