Artificial Intelligence is one of the most rapidly growing technologies which is finding its way into almost every important industry. And while this advancement has proven to reap some really good results, there are some risks that are associated with over-reliance on AI that we need to manage before it all gets out of our hands.
Deep fakes, security threats, joblessness, and other concerns have already emerged at an alarming rate, making it critical to manage the risks associated with AI to ensure its ethical, responsible, and safe deployment.
Nevertheless, since AI has done so much good and because many of its issues can be resolved by AI itself, there is no way for us to stop depending on it. The best move is to manage the risks while deploying AI. Here are some ways we can manage the risks associated with Artificial Intelligence.
Strategies for Managing AI Risks
Ethical Frameworks and Guidelines
At the end of the day, AI is just another technology developed by man to help himself ease his tasks. Its ethical development and deployment are thus in our control. An example, in this case, would be the impact of Artificial Intelligence on school learning. Recently, it has been observed that students have been using tools such as Chat GPT and others to complete their assignments which negatively impacts their learning abilities.
However, if we look back in time, it is not much different from using calculators for math homework or school computers to learn about the latest technology. Thus, AI assistants are not really the problem here. The problem is the lack of ethical frameworks and guidelines.
Many frameworks have already been developed in this regard such as the IEEE Global Initiative of Autonomous and Intelligent Systems which ensures that every stakeholder involved in the design and development of autonomous and intelligent systems is educated, trained, and empowered to prioritize ethical considerations so that these technologies are advanced for the benefit of humanity.
To ensure ethical AI implementation, every organization must keep the framework in mind while developing and deploying AI solutions.
Robust Data Governance
Identity theft is one of the most serious forms of crime affecting not only individuals but entire nations. According to a recent FTC report, over 1.4 million identity theft cases have been reported, which requires immediate attention. Since the root cause of crimes like identity theft is unauthorized access to data, there must be a robust data governance system in place.
There needs to be a uniform approach to handle both structured and unstructured data available on multiple sources; on the cloud, and on-premises across IoT-enabled devices as otherwise, a mismanaged data would pave the way for an unprecedented level of attacks to breach intellectual property and data. Businesses must recognize the importance of implementing data governance controls and taking a transparent yet systematic approach to handle all types of data.
Here, it is also worth mentioning that there is a risk associated with the collection and storage of critical data in sectors that deal with it frequently, such as the telecommunications sector. As a result, it is critical to rely on ISPs known for their secure infrastructure and who prioritize their customers’ safety, such as Kinetic Internet. Windstream’s Kinetic Internet Security creates a secure network in your home that protects all internet-connected devices while also tracking any criminals who may be after your data.
Bias Detection and Mitigation
One of the major risks associated with AI is that it may reflect or even worsen existing biases reflective of historical and societal injustices. This occurs because AI models are very sophisticated; they scan massive amounts of textual and graphical data and analyze it to find patterns in human language.
When you ask AI a question, for instance, it examines the words you use and searches for chunks of text associated with those words. It lacks context for the questions you pose or the information you provide. In this way, AI models inherit any prejudices ingrained into the text on which they are trained.
AI models must thus be taught to distinguish between fact and fiction by instilling human values and higher-level reasoning in them.
Conclusion
Artificial Intelligence is one of the major technological breakthroughs that has brought some revolutionary changes in almost every field of our life. But in order to use the technology securely, we need to manage the risks associated with AI and ensure its responsible and beneficial use. Organizations and policymakers must implement the strategies and recommendations provided to navigate the complexities of AI risk management.