AI shapes people's lives on a daily basis, setting prices in retail stores and making recommendations ranging from movies to romantic partners. But some question whether AI can become a corrupting force, even influencing people's behavior to the point that they break ethical rules. A fascinating study published by researchers at the University of Amsterdam, Max Planck Institute, Otto Beisheim School of Management, and the University of Cologne aims to discover the degree to which AI-generated advice can lead people to cross moral lines. In a large-scale survey leveraging OpenAI's GPT-2 language model, the researchers found AI's advice can "corrupt" people even when they're aware the source of the advice is AI. Academics are increasingly concerned that AI could be co-opted by malicious actors to foment discord by spreading misinformation, disinformation, and outright lies. In a paper published by the Middlebury Institute of International Studies' Center on Terrorism, Extremism, and Counterterrorism (CTEC), the coauthors find that GPT-3, the successor to GPT-2, could reliably generate "informational" and "influential" text that might "radicalize individuals into violent far-right extremist ideologies and behaviors."

Nowadays, we see recommendation systems everywhere. When you buy something in an online marketplace like Amazon, eBay, or any other place, they suggest similar products. On Netflix or youtube, you see the suggestions on your homepage similar to your previous activities or searches. They all follow this one idea. That is they take data from your previous activities and run a similarity analysis.

Earlier we saw many data science applications. Today we will see the diverse data science use cases. We will take examples of social media, e-commerce, transportation, and healthcare to demonstrate some of the important data science use cases in contemporary industries. Stay updated with latest technology trends Join DataFlair on Telegram!! Data Science has brought another industrial revolution to the world. Every industry in this world requires data.

Although artificial intelligence has been around for a while, it was always thought of as something that is in the early stages of development, and that it would take decades before we could make it work to our advantage. In other words, it was the stuff we would usually see in sci-fi movies. However, artificial intelligence has made some huge leaps, and it's definitely here to stay if we were to look at the numbers. According to research, the artificial intelligence market is set to reach $266.92 billion by 2027, which is nearly ten times more than the $27.23 billion that it was worth in 2019. Furthermore, according to recent surveys, 91.5% of top businesses have stated that they are currently investing in AI.

Every evening last summer, after I'd shut down my work laptop, my 3-year-old daughter and I would approach our Google Home smart speaker and yell, "Hey Google, can you play'Aankh Marey' from the movie Simmba?" We'd hold our breaths and wait for a response. The digital assistant would then repeat the name of the Bolly wood song we'd requested in its default standard American accent. We'd rejoice and dance when the assistant played the right number, which happened about half the time. My daughter was going to a Bollywood dance class and we'd finally found a use for the device that my husband had won at a tech conference. Often, however, it would mishear our requests and play something else.

The application of Artificial Intelligence has made its way into every field possible. From the healthcare industry to the entertainment sector, AI has proved to be one of the most widely used technologies today. If you grew up in the 2000s, you grew up reading or watching the Harry Potter series or hearing the series. Most Harry Potter fans have already read The Cursed Child and A Journey through the history of Magic and are now looking for something new to read. These Potterheads now have something new to read, brought to them by an AI-generated text prediction.

In recent years, the'maker movement' has emerged as a social phenomenon driven by novel technological possibilities.1 With the help of inexpensive, yet highly versatile means of production (for example, CNC milling machines, 3D printers) and easy-to-use software tools, makers free themselves from their traditional role as passive consumers and evolve into innovators and producers. Although the act of physical production seems to be at the center of the movement, a large part of the creative work takes place in the online sphere. These digital activities and their outcomes provide a rich source of information that can be used to gain a more nuanced understanding of how the digitization affects the creative process itself. Of all the production methods available to makers, 3D printing is probably the most versatile and requires only a limited understanding of the production process. Several 3D design software packages allow even lay people to turn their ideas into printable designs.

Synthetic media technologies are rapidly advancing, making it easier to generate nonveridical media that look and sound increasingly realistic. So-called "deepfakes" (owing to their reliance on deep learning) often present a person saying or doing something they have not said or done. The proliferation of deepfakesa creates a new challenge to the trustworthiness of visual experience, and has already created negative consequences such as nonconsensual pornography,11 political disinformation,19 and financial fraud.3 Deepfakes can harm viewers by deceiving or intimidating, harm subjects by causing reputational damage, and harm society by undermining societal values such as trust in institutions.7 What can be done to mitigate these harms?

Seeking to call into question the mental acuity of his opponent, Donald Trump looked across the presidential debate stage at Joseph Biden and said, "So you said you went to Delaware State, but you forgot the name of your college. Biden chuckled, but viewers may have been left wondering: did the former vice president misstate where he went to school? Those who viewed the debate live on an app from the London-based company Logically were quickly served an answer: the president's assertion was false. A brief write-up posted on the company's website the next morning provided links to other fact-checks from National Public Radio and the Delaware News Journal on the same claim, which explain that Biden actually said his first Senate campaign received a boost from students at the school. Logically is one of a number of efforts, both commercial and academic, to apply techniques of artificial intelligence (AI), including machine learning and natural language processing (NLP), to identify false ...

Human-in-the-loop machine learning is widely used in artificial intelligence (AI) to elicit labels for data points from experts or to provide feedback on how close the predicted results are to the target. This simplifies away all the details of the decision-making process of the expert. In this work, we allow the experts to additionally produce decision rules describing their decision-making; the rules are expected to be imperfect but to give additional information. In particular, the rules can extend to new distributions, and hence enable significantly improving performance for cases where the training and testing distributions differ, such as in domain adaptation. We apply the proposed method to lifelong learning and domain adaptation problems and discuss applications in other branches of AI, such as knowledge acquisition problems in expert systems. In simulated and real-user studies, we show that decision rule elicitation improves domain adaptation of the algorithm and helps to propagate expert's knowledge to the AI model.