AI is all around us, from our personalized feeds on social media to Siri, Google Assistant, Alexa, and other virtual assistants. However, as AI permeates our daily life, it is crucial to consider the potential harms and risks that it could pose, especially when it comes to bias and safety.
AI systems are only as good as the data they are trained on. Therefore, if that data is biased, it's pretty easy to predict that so will the AI. For example, facial recognition systems have higher error rates for people with darker skin. This is due to the paucity of images of people of color being used for training these models.
Also, some algorithms used in criminal justice systems are often biased against minority groups. These biases could have serious consequences, causing discrimination and social inequality.
The second side of this conversation is the topic of AI Safety. There are numerous risks associated with AI. Measures, therefore, need to be put in place to safeguard against such harm.
Malicious people can use deepfake technology to create highly realistic but fabricated content. This can range from videos, and images to audio. They can use these to spread misinformation, deception, and distrust.
Malicious agents can use AI-powered audiovisual doctoring to modify and manipulate private and personal content. Such images and videos can be doctored without the owner's consent. This can lead to privacy violations and security breaches.
Using AI for deepfake and audiovisual doctoring can raise legal and ethical implications, such as copyright infringement, intellectual property rights, and data privacy.
AI for deepfake and audiovisual doctoring can lead to emotional and psychological impacts, such as anxiety, depression, and trauma, especially when used to harass, bully, or intimidate individuals.
Researchers and AI companies are developing approaches to address this bias. Some of the methods include:
By using more diverse training data that includes a variety of perspectives, experiences, and backgrounds, we can help ensure that AI is more accurate and less biased.
This includes making the data and algorithms used in AI systems more transparent so that users can understand how the AI works and what data it uses. This approach also includes implementing accountability measures, such as audits and oversight, to ensure that AI systems are developed and used responsibly.
Bias audits involve testing AI systems for bias and identifying areas where discrimination may exist. We can achieve this by analyzing the data and algorithms used in the AI system, as well as by testing the AI system against different groups of people. By conducting bias audits, we can identify and address any biases that may be present in AI systems.
Another potential approach to addressing AI bias is requiring warning labels for AI products. Warning labels would inform users of the potential risks and harms associated with using the AI product, such as the potential for bias, discrimination, or privacy violations. This would allow users to make more informed decisions about whether or not to use the AI product and encourage AI companies to develop and use AI responsibly.
It is safe to say using AI without warning labels can have significant consequences on your health and identity. For example, a jealous ex can create a deepfake video of his partner, merge it into a pornographic video and post it online to scorn her. This can lead to a gamut of problems for the innocent girl.
That example is on an individual level; it could be used for political manipulation and spreading misinformation. One can create a deepfake of a political opponent making career-ending utterances.
Similarly, the new Glamour mode on TikTok, which uses AI to smooth out imperfections in users' faces, has been criticized for promoting unrealistic beauty standards and erasing individuality. Hypothetically, one may never actually know the true you if you rely heavily on such trends. This highlights the potential for AI to alter our sense of self and identity.
AI is a powerful technology that has the potential to bring myriads of benefits to society. However, it also poses significant risks and challenges. By identifying bias in AI, implementing safety measures such as warning labels, and promoting transparency and accountability, we can ensure that AI is safely used.