AI guarantees fraud in all facets of life.

AI reflects the motives and opinions of the person or people using the technology. Bad actors can use the technology to intentionally deceive, manipulate, or harm others. Users with good intentions can unknowingly do the same, because we all have unconscious bias, and AI absorbs those biases during its training. Following are a handful of situations that show how AI can be harmful and affirm the need for governance.

AI can be used to create convincing deepfakes, which are doctored images, audio, or video that look and sound real. These fake media are then used to spread misinformation, typically to manipulate or trick people into certain beliefs or behaviors.

Cyber attackers are increasingly using AI tools to make their attacks smarter and more automatic. Things like data poisoning, or reverse engineering have been used to carry out targeted cyber-attacks. For example, an attacker might use a chatbot to write fake messages that look real and don’t have obvious mistakes like spelling errors to trick people.

AI models have generated discriminatory outcomes against certain people/groups of people in the past. One of the common examples in the lending domain is an AI-based credit scoring model to approve or reject loans. In one such scenario, African American and Hispanic people got fewer loans than white people. This happened because the data used to make lending decisions had unfair biases. To make things better, we need to use more diverse data and the efficient use of fairness techniques to make the data usable.

Bad actors are increasingly using AI-based techniques to carry out financial fraud that results in financial losses for investors and loss of trust in financial institutions. One common example is the use of fake news and sentiment (both positive and negative) to influence the prices of specific stocks by creating inflated demand/supply to make a quick profit. This emphasizes the need to have adequate financial market surveillance tools that can monitor employees’ trading and communication data to detect unusual patterns and deviations before fraud happens.

Governments and organizations are increasing the use of AI-powered surveillance tools and techniques to monitor people, raising questions about data privacy and security. People are worried about how their personal information is used and how much is being used.