https://workyoucanexplain.com/tags/ai-literacy/ Recent content in AI Literacy on Work You Can Explain Hugo en-US Copyright © Work You Can Explain Thu, 03 Sep 2026 00:00:00 -0500 https://workyoucanexplain.com/posts/protect-student-data-before-sharing-with-ai/ Thu, 03 Sep 2026 00:00:00 -0500 https://workyoucanexplain.com/posts/protect-student-data-before-sharing-with-ai/ <p>Before sending a document, screenshot, log, dataset, or source file to an AI service, reduce the request to the minimum permitted evidence. Replace real values with synthetic equivalents when possible. Remove direct and indirect identifiers. Inspect filenames, metadata, and surrounding context. Then review the exact outgoing input.</p> <p>If the task still requires restricted or sensitive material after that pass, do not treat redaction as automatic permission. Use an approved institutional route or ask an authorized person.</p> https://workyoucanexplain.com/posts/find-ai-information-through-builders-not-influencers/ Mon, 24 Aug 2026 00:00:00 -0500 https://workyoucanexplain.com/posts/find-ai-information-through-builders-not-influencers/ <p>When an AI topic becomes noisy, do not begin by following the loudest account. Use commentators and aggregators to discover questions, find builders or practitioners who have done relevant work, trace the material claim to primary evidence, and record the conditions that limit your conclusion.</p> <p>“Builder” is a role in relation to a claim, not a popularity score. A researcher, maintainer, operator, educator, or domain practitioner may be a builder when their relevant work can be inspected or described. A confident personal brand is not enough.</p> https://workyoucanexplain.com/posts/is-a-computer-science-major-worth-it-in-the-ai-era/ Thu, 30 Jul 2026 00:00:00 -0500 https://workyoucanexplain.com/posts/is-a-computer-science-major-worth-it-in-the-ai-era/ <p>A computer science major can still be worth it in the AI era, but the title of the degree is not enough. A strong program gives you a coherent foundation, repeated technical practice, feedback, mentors, peers, projects, and access to opportunities that would be difficult to assemble alone.</p> <p>AI does change the decision. It can reduce the effort required to produce some code, and it changes how software work is divided. It does not remove the need to define a problem, understand systems, evaluate evidence, test behavior, protect data, maintain software, and explain decisions.</p> https://workyoucanexplain.com/posts/how-to-follow-important-ai-updates/ Tue, 28 Jul 2026 00:00:00 -0500 https://workyoucanexplain.com/posts/how-to-follow-important-ai-updates/ <p>Follow AI updates by monitoring the questions, tools, and rules that already affect your work. Do not try to follow the whole field. Keep a small register of first-party sources, review it at a fixed time, and investigate only changes that could alter a real course or workflow.</p> <p>The output of the review is a decision, not a larger reading list. For each material update, decide to <strong>ignore</strong>, <strong>monitor</strong>, <strong>trial</strong>, or <strong>adopt</strong>.</p> https://workyoucanexplain.com/posts/structured-languages-as-thinking-tools-in-the-ai-era/ Tue, 28 Jul 2026 00:00:00 -0500 https://workyoucanexplain.com/posts/structured-languages-as-thinking-tools-in-the-ai-era/ <p>Structured languages help you think by forcing some decisions into visible forms. A heading names a section. A table requires columns. A schema defines allowed shapes. A program turns a procedure into operations that can be run.</p> <p>None of these forms guarantees a correct result. They make selected assumptions, boundaries, and failure cases easier to inspect. Use natural language for intent, context, uncertainty, and negotiation. Add structure where explicit rules and mechanical checks improve the work.</p> https://workyoucanexplain.com/posts/desirable-talents-in-the-ai-era/ Tue, 28 Jul 2026 00:00:00 -0500 https://workyoucanexplain.com/posts/desirable-talents-in-the-ai-era/ <p>Three human talents are worth deliberate practice alongside AI: broad foundations, initiative, and mental robustness.</p> <p>This is a practice framework, not a prediction about which jobs will grow or which personality will succeed. The value is immediate. These talents help a student frame better questions, begin worthwhile work, respond to evidence, and remain responsible for AI-assisted results.</p> <p>Treat them as skills. Build them through dated artifacts and observable actions, not labels such as “well-rounded,” “self-starter,” or “resilient.”</p> https://workyoucanexplain.com/posts/choose-text-and-data-formats-for-people-software-and-llms/ Sun, 26 Jul 2026 00:00:00 -0500 https://workyoucanexplain.com/posts/choose-text-and-data-formats-for-people-software-and-llms/ <p>Choose a format from the interface contract, not from claims that one syntax is universally best for people, software, or LLMs. Identify the authoritative consumer, information that must survive, available validators, likely errors, and recovery path. Then test the actual workflow.</p> <p>A useful default is:</p> <ul> <li>Markdown for human-readable structured documents;</li> <li>JSON for typed data exchange;</li> <li>XML when named nested boundaries and an existing XML ecosystem matter;</li> <li>YAML for human-maintained configuration when its rules are understood;</li> <li>CSV for one simple table; and</li> <li>ordinary prose when no program must parse the structure.</li> </ul> <p>These are starting points, not rankings.</p> https://workyoucanexplain.com/posts/academic-integrity-in-the-age-of-ai/ Fri, 24 Jul 2026 00:00:00 -0500 https://workyoucanexplain.com/posts/academic-integrity-in-the-age-of-ai/ <p>There is no universal rule for acceptable AI assistance. The controlling rules come from the assignment, course syllabus, instructor, department, institution, and applicable data policy. Read them before using AI, and ask the instructor when the boundary is unclear.</p> <h2 id="start-with-the-learning-objective">Start with the learning objective</h2> <p>AI tutoring supports the student&rsquo;s learning when it helps the student perform the required thinking. Prohibited substitution occurs when the tool performs work the student is expected to produce independently.</p> https://workyoucanexplain.com/posts/dont-let-a-useful-ai-conversation-disappear/ Fri, 24 Jul 2026 00:00:00 -0500 https://workyoucanexplain.com/posts/dont-let-a-useful-ai-conversation-disappear/ <p>A useful AI conversation is not durable documentation. It may contain false starts, hidden context, private information, and conclusions that only make sense inside the exchange. Capture the verified lesson in your own record.</p> <h2 id="record-the-problem">Record the problem</h2> <p>State the original objective, starting state, constraints, and exact failure or question. Include software versions, current directory, input shape, and error text only when relevant and safe.</p> <p>Do not begin with “AI fixed it.” A future reader needs the technical problem.</p> https://workyoucanexplain.com/posts/the-capture-verify-crystallize-loop/ Fri, 24 Jul 2026 00:00:00 -0500 https://workyoucanexplain.com/posts/the-capture-verify-crystallize-loop/ <p>An AI-assisted result becomes reusable only after it works without the conversation. Use a three-stage loop: capture the result and context, verify the claims and behavior, then crystallize the confirmed lesson into the smallest useful asset.</p> <h2 id="capture-enough-context">Capture enough context</h2> <p>Begin with the learning record:</p> <ul> <li>objective and starting state;</li> <li>constraints and policy boundary;</li> <li>attempted steps;</li> <li>result that appeared successful;</li> <li>material AI assistance;</li> <li>risks and assumptions; and</li> <li>evidence still needed.</li> </ul> <p>Capture is not endorsement. It prevents important context from disappearing before review.</p>