7 minute read
THE AI RENAISSANCE IN INVESTIGATIONS
Is fiction meeting reality?
Dean Benard, President and CEO Benard + Associates
Have you ever watched a movie and thought, “Wait! We have that now!
We can do that!” Let’s consider Minority Report and Mission Impossible. These two movies provide compelling foreshadowing of potential Artificial Intelligence (AI) applications in investigations. Both films showcase futuristic technologies that resonate with the real-world development of AI tools, particularly in the context of predictive analytics, evidence gathering, and ethical challenges in investigations.
The integration of AI into investigative processes is not just a fictional vision anymore; it is quickly becoming a reality. As we strive to uphold standards, protect the public, and maintain trust in various professions, AI offers tools that can enhance our efficiency and accuracy. However, with these advancements come challenges that require our careful consideration.
In my upcoming talk for the AI In Regulation Conference: Global Perspectives and Local Leadership, I will explore how AI will reshape investigations and introduce the opportunities and ethical dilemmas that come with this technology. For now, consider this article a primer for what’s to come as I describe sev- eral AI applications we might soon see in practice.
Predictive risk modeling: Anticipating issues before they arise
Traditionally, regulatory investigations, have been reactive, addressing issues as they surface. AI can potentially shift this paradigm by enabling predictive risk modeling, allowing us to forecast potential violations based on historical data (Yes kind of like Minority Report). For instance, in healthcare, AI can analyze billing patterns to identify anomalies indicative of fraud, enabling early intervention and prevention of significant harm. This proactive stance is applicable across various professions, from law to engineering, where early detection of non-compliance can prevent escalation. However, as exciting as this technology is, it requires a delicate balance between innovation and fairness. We must question the accuracy of these predictions and establish safeguards to prevent false positives or undue targeting. Predictive tools can only be valuable if they enhance, not replace, our commitment to justice and equity.
Bias detection: Upholding fairness in our processes
Let’s face it: bias is a part of being human. It creeps into our investigative reports, sometimes in ways that we don’t even realize. AI offers a fascinating solution by analyzing text for subtle biases that may escape human reviewers. Through natural language processing (NLP), AI identifies patterns in language that suggest prejudice, favoritism, or stereotyping. Take, for example, a misconduct investigation.
AI might flag language like describing a complainant as “emotional” while calling a respondent “confident.”
Such descriptors can subtly influence perceptions decision makers generate about the parties. By highlighting these biases, AI ensures reports remain neutral and focused on facts. This isn’t just about catching mistakes; it’s about reinforcing our commitment to fairness. With proper training and transparency, AI can help us eliminate unintentional bias, ensuring that everyone involved in an investigation is treated equitably.
Dynamic case prioritization: Allocating resources where they matter most
In regulatory work, not all cases are created equal. Some demand immediate attention due to public safety concerns, while others carry less urgency. AI-driven dynamic case prioritization enables us to allocate resources effectively by scoring cases based on criteria like severity and public interest. For instance, a minor licensing infraction might rank lower than a case involving professional misconduct that risks harm to clients. By automating this process, AI allows us to focus on high-impact cases, improving efficiency without sacrificing thoroughness. That said, we must approach this technology cautiously. What criteria should drive prioritization? How do we ensure transparency in these algorithms? We have seen criticism of regulators in the past where these types of decisions were alleged to have been poorly implemented, and that was when humans did it!
Tackling deepfakes: Ensuring the integrity of digital evidence
If you haven’t encountered a deepfake yet, let me tell you—they’re as impressive as they are alarming. These hyper-realistic forgeries of video, audio, or images are already complicating our lives. Imagine a video submitted as evidence showing a professional behaving inappropriately during a consultation. It looks real, but AI video authentication tools might detect unnatural blinking patterns or inconsistent lighting, exposing it as a deepfake. Deepfakes highlight the necessity of advanced detection tools in maintaining the integrity of digital evidence. But they also remind us of the catand-mouse game between technology and those who seek to manipulate it. Staying ahead of these developments is crucial.
AI as a Witness: Navigating ethical dilemmas
Now let’s talk about what might seem like science fiction but is closer than you think: AI as a “digital witness.” Imagine AI systems monitoring professional interactions and flagging potential misconduct in real-time.
This might sound outrageous to some and appealing to others, but it also raises ethical questions about privacy, data ownership, and accuracy. Looking at it from the regulated professional’s side, we are currently seeing digital note taking programs in use, ostensibly to save time and create greater efficiency, but what about using AI technology to monitor activities as a type of defensive practice against potential fabricated complaints. Will we eventually see AI chaperones in rooms rather that other people?
The Shocking and the Speculative: Future possibilities
The possibilities are almost exponential as we consider AI applications. Emerging technologies are exploring neural signal interpretation, yes, reading brain activity. Imagine AI detecting dishonesty or intent based on neural patterns. While this remains largely theoretical, the implications are staggering. Then there’s the idea of “digital regulators.” These systems could autonomously handle tasks like ensuring professionals meet licensing requirements. But what happens when AI misinterprets ambiguous rules? This tension between automation and nuance will undoubtedly have a major impact on the future of regulation.
It's not just about looking forward
In the discussion about AI the focus is often on how we can do things more efficiently and be proactive in our work, and how we guard against unscrupulous use of AI. However, AI can also be used to research and create strategies and inform operational decisions, and policy. The dynamic case prioritization mentioned earlier is a means of making decisions, but AI can also be used to analyze thousands of past cases and outcomes to assist in establishing the criteria that might be used to determine prioritization. AI could analyze all past cases, and their outcomes then provide a clear history of decisions to measure historical consistency in decision making, as well as inform new decisions as part of an effort to make consistent decisions in cases concerning similar issues and even evidence.
The AI — human partnership
Just as Minority Report showed us a world where crimes could be predicted and Mission Impossible dazzled us with its use of cutting-edge technology to expose deception, we find ourselves standing at the intersection of innovation and reality.
AI is no longer a cinematic fantasy; it’s becoming an integral partner in our efforts to ensure fairness and integrity in investigations. However, as those movies also warned, technology comes with risks and ethical complexities. As we adopt AI to enhance efficiency, uncover hidden patterns, and protect the public, we must remain vigilant to its limitations and potential misuse.
Like the heroes of these films, our mission - should we choose to accept it - is to harness AI’s power responsibly, keeping humanity and justice at the core of every decision.
The future may feel like science fiction, but it’s ours to shape. Let’s meet this challenge head-on, equipped with both curiosity and caution.
