 |
|
|
|||||
Police are getting a boost from artificial intelligence, with algorithms now able to draft police reports in minutes. The technology promises to make police reports more accurate and comprehensive, as well as save officers time. The idea is simple: Take the audio transcript from a body camera worn by a police officer and use the predictive text capabilities of large language models to write a formal police report that could become the basis of a criminal prosecution. Mirroring other fields that have allowed ChatGPT-like systems to write on behalf of people, police can now get an AI assist to automate much dreaded paperwork. The catch is that instead of writing the first draft of your college English paper, this document can determine someones liberty in court. An error, omission, or hallucination can risk the integrity of a prosecution or, worse, justify a false arrest. While police officers must sign off on the final version, the bulk of the text, structure, and formatting is AI-generated. Whoor whatwrote it Up until October 2025, only Utah had required that police even admit they were using an AI assistant to draft their reports. On Oct. 10, that changed when California became the second state to require transparent notice that AI was used to draft a police report. Governor Gavin Newsom signed SB 524 into law, requiring all AI-assisted police reports to be marked as being written with the help of AI. The law also requires law enforcement agencies to maintain an audit trail that identifies the person who used AI to create a report and any video and audio footage used in creating the report. It also requires agencies to retain the first draft created with AI for as long as the official report is retained, and prohibits a draft created with AI from constituting an officers official statement. The law is a significant milestone in the regulation of AI in policing, but its passage also signifies that AI is going to become a major part of the criminal justice system. If you are sitting behind bars based on a police report, you might have some questions. The first question that Utah and California now answer is Did AI write this? Basic transparency that an algorithm helped write an arrest report might seem the minimum a state could do before locking someone up. And, even though leading police technology companies like Axon recommend such disclaimers be included in their reports, they are not required. Police departments in Lafayette, Indiana, and Fort Collins, Colorado, were intentionally turning off the transparency defaults on the AI report generators, according to an investigative news report. Similarly, police chiefs using Axons Draft One products did not even know which reports were drafted by AI and which were not because the officers were just cutting and pasting the AI narrative into reports they indicated they wrote themselves. The practice bypassed all AI disclaimers and audit trails. The author explains the issues around AI-written police reports in an interview on CNNs Terms of Service podcast. Many questions Transparency is only the first step. Understanding the risks of relying on AI for police reports is the second. Technological questions arise about how the AI models were trained and the possible biases baked into a reliance on past police reports. Transcription questions arise about errors, omissions, and mistranslations because police stops take place in chaotic, loud, and frequently emotional contexts amid a host of languages. Finally, trial questions arise about how an attorney is supposed to cross-examine an AI-generated document, or whether the audit logs need to be retained for expert analysis or turned over to the defense. Risks and consequences The significance of the California law is not simply that the public needs to be aware of AI risks, but that California is embracing AI risk in policing. I believe its likely that people will lose their liberty based on a document that was largely generated by AI and without the hard questions satisfactorily answered. Worse, in a criminal justice system that relies on plea bargaining for more than 95% of cases and is overwhelmingly dominated by misdemeanor offenses, there may never be a chance to check whether the AI report accurately captured the scene. In fact, in many of those lower-level cases, the police report will be the basis of charging decisions, pretrial detention, motions, plea bargains, sentencing, and even probation revocations. I believe that a criminal legal system that relies so heavily on police reports has a responsibility to ensure that police departments are embracing not just transparency but justice. At a minimum, this means more states following Utah and California to pass laws regulating the technology, and police departments following the best practices recommended by the technology companies. But even that may not be enough without critical assessments by courts, legal experts, and defense lawyers. The future of AI policing is just starting, but the risks are already here. Andrew Guthrie Ferguson is a professor of law at George Washington University. This article is republished from The Conversation under a Creative Commons license. Read the original article.
Category:
E-Commerce
The workplace AI narrative has been dominated by fears of human replacement. But forward-thinking leaders are discovering AI’s real power: helping employees become more human, not less. Shifting from workplaces of human doings to a collective of activated human beings. And while AI can absolutely help eliminate busywork, opening employees time for more impactful work and meaningful progress, its impact can go far beyond productivity. In fact, having studied power shifts in modern workplaces for many years, I think the companies that will thrive moving forward will focus more on using these tools to improve employee well-being. Smart leaders should approach AI implementation through what I call “human-first integration”using technology to restore conditions where people can do their best thinking, creating, and collaborating. Here are a few use cases you might not have thought of for AI that can help your employees feel more supported in work and life. 1. Make it easier to understand benefits AI can create “invisible support systems” that proactively connect employees with resources without navigating complex HR systems or overcoming the stigma of asking for help. Most employees leave thousands of dollars in wellness stipends, EAP services, and professional development funds unused simply because they don’t understand what qualifies or how to access them. AI is great at analyzing individual situations (e.g., project stress, family circumstances mentioned in calendar entries, or expressed career goals) and suggesting relevant solutions with eligibility and application guidance. A custom GPT can be built, either in-house or via an AI consultant, by uploading a companys benefits guides, policies, and FAQs into an organizations private OpenAI workspace, where access can be limited to employees only. By giving the GPT simple instructions like Answer employee questions about benefits in plain language, the tool becomes an easy, secure way for staff to get clear and consistent answers about their benefits. 2. Create safe reporting for workplace harm Traditional HR reporting makes employees navigate complex hierarchies and risk retaliation. AI-powered anonymous reporting systems can collect detailed incident information, identify patterns across reports, and route concerns to appropriate parties while protecting reporter identity. For example, AllVoices is an AI-fueled employee relations platform that offers an employee relations copilot, a whistleblower hotline and an anonymous reporting tool to build trust and safety while also encouraging a culture of speaking up when something is wrong. The beauty is the AI is customized to the organizations systems, processes, and needs then it gathers anonymous incident information, can guide employees through the submission process and offer supportive resources, but doesnt make decisions that stays within human control. 3. Establish low-risk feedback loops Implement micro-feedback through check-ins triggered by specific events like meetings, high-stress phases, or team restructuring. This enables real-time pattern recognition and intervention before problems escalate. In my work coaching teams, I’ve seen how powerful this intentional ongoing approach can be as it shifts behavior from dreading the heavy annual review grading system to small lift, routine experiences of being heard and valued. I gather insights from individual coaching sessions and share aggregated themes with leadership, protecting individual privacy while surfacing patterns to help address systemic challenges before they become widespread problems. While AI wont be able to reach the same level of depth and nuance as live coaching with a human would, the ability to automate checkpoints that are incorporated in larger team strategy will build trust and reduce fear of experience sharing. Try leveraging engagement platforms like CultureAmp that use AI to facilitate a continuous feedback loop by automating the delivery of pulse surveys (short, focused check-ins that can be triggered by specific events), providing real-time sentiment and theme analysis of the results, and recommending next steps. 4. Act on early warning signs for interpersonal conflict AI can analyze communication patterns and misunderstandings before tension becomes destructive. It can suggest resolution approaches, connect people with mediation resources, and track effectiveness. Most importantly, AIs ability to identify and interrupt microaggressions can help recipients validate perceptions and educate those causing unintentional harm. Opre is an AI-driven platform that uses meeting notes and other ongoing communications to provide professional development recommendations and recognize friction points. WorkHuman offers an Inclusive Advisor feature that identifies and mitigates unconscious bias in real-time. 5. Support self-discovery and team understanding I often guide clients through what I call mesearch, a process of identifying a personalized leadership profile through assessments and reflection that equips them with language to describe their authentic leadership style. Now, imagine an AI platform extending this process across an entire team, enabling people not only to articulate their strengths but also to understand and align with those of their colleagues, while intelligently matching roles in complex situations so energy and efforts are optimized to meet challenges successfully. For instance, if your team has taken assessments like the Clifton Strengths, DISC, Myers-Briggs, Predictive Index or HBDI, you can prompt your AI platform to take the assessment findings of each team member and identify where your team is likely to collectively shine. Think: Who will work best together in various scenarios, where strengths overlap and potential gaps may be, and where their diverse perspectives will benefit an initiative. This is great for staffing projects, assigning mentors, and for intentional hiring decisions to build a robust, resilient team. Machines Supporting Humans Organizations thriving in the coming decade won’t use AI most extensively, but most intentionally. This requires leaders who understand technology is only as powerful as the human systems it supports. As a mixed-race, millennial woman who has navigated predominantly white, male-dominated industries, I’ve seen how traditional power structures prioritize performance over people. AI gives us a chance to build workplaces that amplify human potential rather tha exploit it. According to McKinsey & Co, over the next three years, 92% of companies plan to increase their AI investments. Gen AI is already here, its up to leaders to embrace this paradigm shifting opportunity effectively. The future isn’t humans versus machinesit’s humans plus machines, creating conditions where people can think, create, and connect in ways that drive both individual fulfillment and organizational success.
Category:
E-Commerce
For decades now, Google has been the unquestioned champion of searchour digital oracle, the first and last stop for every question, from “What’s the best pizza place near me?” to “How many protons are in a carbon atom?” But heres the key difference now: while Google has started to incorporate AI with features like AI Overviews and the new AI Mode, a traditional keyword search is great for finding facts, but not so great at understanding context. It’s like asking a librarian for a book on “dogs” and expecting them to know you really want to know how to train a puppy. You might get a whole library, but you still have to find the right book yourself. That’s where dedicated AI-powered search, whether a self-contained tool like Perplexity or Google’s own conversational AI interface, truly shines. It doesn’t just look for keywords; it understands your intent. It can be a genuine time-saver, and in some cases, it’s just plain better than scrolling through a list of blue links. Here are five times when using an AI to search will give you a better answer than Google. Answers to subjective questions A traditional search engine is fantastic for finding facts, but it falls short when you’re looking for an answer that isn’t black and white. For example, if you Google “best workout routine for a beginner,” you’ll get a list of articles, but you’ll have to read through them to find the one that fits your specific needs. It’s a lot of scrolling and sorting through different opinions. With an AI, you can ask a much more nuanced question, such as: “What’s the best workout routine for a beginner who wants to build strength but has joint pain and a limited amount of time?” The AI can then synthesize information from multiple sources and provide a tailored response that takes all your constraints into account, giving you a comprehensive plan rather than a list of articles to sift through. Explaining complex topics We’ve all been there: you need to explain a complex topic, but the standard online explanations are full of jargon you don’t understand. Or maybe you’re trying to explain a technical concept to a colleague who isn’t as familiar with the subject. Ask an AI to “explain [the concept] in plain English for someone with no background in [the field].” It can take dense, confusing information and distill it into something simple and digestible. You can even ask it to “use a relatable analogy” to make the concept stick. It’s like having a personal tutor who’s always on call. Preparing for meetings and interviews You have an important call with a potential client or a new partner, and you want to go in prepared but digging through their company’s website, recent press releases, and social media feeds for relevant background info is a serious time sink. A simple Google search will give you a bunch of links, but you’ll have to do all the reading yourself. Prompt an AI with something like: “Help me prepare for a call with [Customer Name]. Summarize the top three news stories from the past six months and highlight anything relevant to their business goals.” This gives you a quick, digestible cheat sheet so you can sound informed and confident without spending hours on a deep dive. Kick-starting creative projects Starting from scratch is one of the hardest parts of any creative endeavor. You have to write an outline for a presentation, a script for a video, or even just the agenda for a team meeting, and the blank page feels intimidating. A Google search might give you “presentation outline templates,” but you’ll still have to fill in all the details yourself. Instead, ask an AI to give you a head start. Use a prompt like: “Create a 10-slide outline for a presentation about [topic] for a [target audience], and include a proposed title for each slide.” The AI can give you a solid scaffolding structure to build on, saving you the initial struggle and giving you a foundation to refine and customize. Learning new skills quickly Let’s say you’ve got a new software tool you need to learn for a project, or you’re trying to figure out how to do something you’ve never done before, such as setting up a home server. A traditional search will give you a mix of official documentation, video tutorials, and forum postsall of which you have to piece together yourself. An AI can act kind of like a personal coach. You can ask: “Give me a step-by-step tutorial for setting up a home server, assuming I have no prior experience with networking.” The AI can lay out the process in a clear, linear fashion, and if you get stuck, you can ask follow-up questions for clarification, like “What does ‘port forwarding’ mean in simple terms?” Its a truly interactive and personalized learning experience.
Category:
E-Commerce
All news |
||||||||||||||||||
|
||||||||||||||||||