3.6 Artificial intelligence Questionbank

Sentencing criminals using artificial intelligence (AI)

In 10 states in the United States, artificial intelligence (AI) software is used for sentencing criminals. Once criminals are found guilty, judges need to determine the lengths of their prison sentences. One factor used by judges is the likelihood of the criminal re-offending*.

The AI software uses machine learning to determine how likely it is that a criminal will re-offend. This result is presented as a percentage; for example, the criminal has a 90 % chance of re-offending. Research has indicated that AI software is often, but not always, more reliable than human judges in predicting who is likely to re-offend.

There is general support for identifying people who are unlikely to re-offend, as they do not need to be sent to prisons that are already overcrowded.

Recently, Eric Loomis was sentenced by the state of Wisconsin using proprietary AI software. Eric had to answer over 100 questions to provide the AI software with enough information for it to decide the length of his sentence. When Eric was given a six-year sentence, he appealed and wanted to see the algorithms that led to this sentence. Eric lost the appeal.

On the other hand, the European Union (EU) has passed a law that allows citizens to challenge decisions made by algorithms in the criminal justice system.

* re-offending: committing another crime in the future

Source A

Source B

It is a paradox to brand a technological innovation as tainted goods by its very name. ‘Deepfake’ is a victim of its own capabilities. Negative connotations and recent incidents have pigeonholed this innovation in the taboo zone. The rise of deepfake technology has ushered in very interesting possibilities and challenges. This synthetic media, created through sophisticated artificial intelligence algorithms, has begun to infiltrate various sectors, raising intriguing questions about its potential impact on education and employability.

The dawn of deepfake technology introduces a realm of possibilities in education. Imagine medical students engaging in lifelike surgical simulations or language learners participating in authentic conversations. The potential for deepfake to revolutionise training scenarios is vast and could significantly enhance the educational experience. Beyond simulations, deepfake can transport students to historical events through realistic reenactments or facilitate virtual field trips, transcending the boundaries of traditional education. The immersive nature of deepfake content holds the promise of making learning more engaging and memorable.

Source C

However, while these potential abuses of the technology are real and concerning that doesn't mean we should turn a blind eye to the technology’s potential when using it responsibly, says Jaime Donally, a well-known immersive learning expert.

“Typically, when we're hearing about it, it's in terms of the negative – impersonation and giving false claims,” Donally says. “But really, the technology has the power of bringing people from history alive through old images that we have using AI.”

Donally, a former math teacher and instructional technologist, has written about how a type of deep fake technology called deep nostalgia technology that went viral in 2021 can allow students to form a stronger connection with the past and their personal family heritage. The technology, available on the MyHeritage app, allows images to uploaded that are then turned into short animations thanks to AI technology.

Here are some of the ways in which teachers can utilize deep fake technology in the classroom utilizing the MyHeritage app. Teachers have used the deep fake technology in the My Heritage app to bring historical figures such as Amelia Earhart and Albert Einstein to life. One teacher Donally has communicated with used an animation of Frederick Douglass (above) to help students connect with Douglass’ famous 1852 speech about the meaning of the Fourth of July to Black enslaved Americans. Another teacher has plans to use the app to have students interview a historical figure and create dialogue for them, then match the dialogue to the animation.

Donally herself has paired animations she's created with other types of immersive technology. “I layered it on top in augmented reality,” she says. “When you scan the photo of my grandfather, it all came to life. And it became something that was much more relevant to see in your real-world space.”

With proper supervision, students can use the technology to animate images of family members or local historical figures, and can experiment with augmented reality (AR) in the process. “It makes you want to learn more,” Donally says of animations created using deep fake technology. “It drives you into kind of the history and understanding a bit more, and I think it also helps you identify who you are in that process.”

Source D

Education platforms are harnessing deepfake technology to create AI tutors that provide customised support to students. Rather than a generic video lecture, each learner can get tailored instruction and feedback from a virtual tutor who speaks their language and adjusts to their level.

For example, Anthropic built Claude, an AI assistant designed specifically for education. Claude can answer students’ natural language questions, explain concepts clearly, and identify knowledge gaps.

Such AI tutors make learning more effective, accessible, and inclusive. Students feel like they have an expert guide helping them master new skills and material.

AI and deepfake technology have enormous potential to enhance workforce training and education in immersive new ways too. As Drew Rose, CSO and founder of cybersecurity firm Living Security, explains, “educators can leverage deepfakes to create immersive learning experiences. For instance, a history lesson might feature a ‘guest appearance’ by a historical figure, or a science lesson might have a renowned scientist explaining complex concepts.” Ivana Bartoletti, privacy and data protection expert at Wipro and author of An Artificial Revolution – On Power, Politics and AI envisions similar applications.

“Deepfake technologies could provide an easier and less expensive way to train and visualise,” she says. “Students of medicine and nursing currently train with animatronic robots. They are expensive and require special control rooms. Generative AI and augmented or virtual reality headsets or practice rooms will be cheaper and allow for the generalisation, if not the gamification, of simulation.”

Medical students could gain experience diagnosing and treating simulated patients, while business students could practice high-stakes scenarios like negotiations without real-world consequences. These immersive, gamified environments enabled by AI and deepfakes also have vast potential for corporate training.

Bartoletti notes, “A similar use case could be made for other types of learning that require risky and skill-based experiences. The Air Force uses AI as adversaries in flight simulators, and humans have not beaten the best AIs since 2015.

Machine learning (ML) allows systems to learn from data, enabling applications like image recognition in social media and fraud detection in finance. These applications rely on different types of machine learning, such as supervised learning, where algorithms are trained on labeled data, and unsupervised learning, where systems find patterns without labels.

The Role of Machine Learning in Predictive Policing

Machine learning algorithms are increasingly used in predictive policing to identify potential crime hotspots and allocate resources. While these tools may improve efficiency, concerns exist about bias in crime data, which can lead to unjust targeting of certain communities.

Fake news

We see and hear news every day and trust that the information provided is accurate. That belief may soon end.

Artificial intelligence (AI) software is now being developed that can produce fake video footage of public figures using recordings of their own voices. Using as little as one minute of user-generated content (data), it can reproduce a particular person’s voice. The developer of this software demonstrated the results by using the voices of Bill Clinton, George Bush and Barack Obama in a computer-generated conversation.

Once a person’s voice has been reproduced, a fake video can be created by processing hundreds of videos of the person’s face. Video footage of politicians are often used, as there is so much data available online.

Law professor John Silverman commented that, as humans we tend to believe what we see, and the increased number of tools to make fake media that is unrecognizable from real media is going to prove a major challenge in the future.

The Influence of AI on Political Power and Public Opinion

AI-driven algorithms on social media platforms play a significant role in shaping public opinion by curating political content and advertisements based on users' behavior. While this personalization can engage voters, it also raises concerns about the concentration of power in the hands of tech companies, the spread of misinformation, and the potential manipulation of public opinion.

Robots and autonomous technologies are being deployed in diverse contexts, from industrial robots in factories to virtual assistants in homes. Each type of robot serves a distinct purpose, helping with productivity, service, or social interaction in different sectors.

Ethical Challenges of AI in Hiring and Recruitment

Many companies use AI-driven tools to screen job applicants and rank candidates. While these systems streamline hiring, they can also introduce bias, potentially disadvantaging certain demographic groups. This raises concerns about fairness, transparency, and accountability in AI-driven recruitment.