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Geoffrey Hinton said “become a plumber” if you're worried about AI.
He was only half-joking. But he showed us something important about the future of work.
1. From Execution to Evaluation
Before: You research, analyze, and write reports.
Now: AI generates drafts, you provide critical judgment.
Your value: Knowing what's wrong, not just what's right.
2. From Knowledge to Curation
Before: You needed to know everything in your field.
Now: You need to know which AI outputs to trust.
Your value: Pattern recognition across AI-generated content.
3. From Individual to Orchestrator
Before: You completed tasks solo.
Now: You manage multiple AI agents working simultaneously.
Your value: Strategic thinking about workflow design.
4. From Technical to Ethical
Before: Focus on getting the work done.
Now: Focus on ensuring the work should be done.
Your value: Moral reasoning and consequence evaluation
5. From Production to Innovation
Before: You spent 80% of time on routine tasks.
Now: AI handles routine, you focus on breakthrough thinking.
Your value: Asking questions nobody thought to ask.
Most important skills that will continue to matter
Critical thinking beats technical knowledge. Ethics trump efficiency. Human judgment remains irreplaceable. At least for the next little while
So, what does our future look like?
AI won’t steal your job by default. But someone using AI better than you might. The difference isn’t technical skills. It’s knowing when to trust the machine and when to override it. The entry level is disappearing, and instead, we are training to orchestrate tasks together with our artificial buddies.
What skill are you developing to stay ahead of the AI curve? Let us know in the comments.
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In the episode 5 of the AI Academics Podcast, hosted by Professor Dr. Lennart Nacke and his co-host Vugar Ibrahimov, the duo discusses AI's role in generating creative chess pieces, AI tools for reading academic papers, and evolving internet behaviour influenced by AI. The episode also emphasizes ethical integration and effective use of AI tools, concerns about data privacy, and the future of AI-driven search engines. The team highlights their AI research tools webinar and encourages listeners to explore their Substack and Medium writings for more insights.
00:00 Welcome to the AI Academics Podcast
00:20 Black Friday and Cyber Monday Deals
00:59 Gen Chess: A Creative AI Experiment
04:27 Exploring 11 Reader and GenFM
05:53 Notebook LM and Privacy Concerns
18:54 Generative AI in Browsers
24:33 The Future of AI-Powered Search
27:35 Wrapping Up and Webinar Promotion
In this episode, I chat with Vugar Ibrahimov to explore how AI is reshaping academic writing. We dive into practical tools like Napkin AI for creating social media content, and discuss the double-edged sword of AI writing assistance - from improving productivity to potentially dulling our writing skills. Our conversation takes interesting turns as we debate AI's role in creativity and critical thinking, explore ethical considerations, and share insights on using AI tools effectively while preserving human creativity in our work. We also tackle the growing concern of over-reliance on AI and discuss strategies for maintaining a healthy balance between human and machine input in academic writing.
You sit at your desk. Fingers hovering over the keyboard. The human prompts, the machine responds. ChatGPT stares back at you. The cursor waits while ChatGPT thinks. That rainbow wheel is doing more loops than a rollercoaster having an existential crisis. You type a prompt, but the response misses the mark completely. Sound familiar?
AI tools transform how we work—but only if we know how to talk to them. Think of prompting as learning a new language. You wouldn’t walk into a French café and expect perfect service with broken phrases from your high school textbook. The same goes for AI. Let us show you how to order exactly what you want.
Context shapes meaning
And meaning creates context. Most self-proclaimed AI experts write prompts like they’re sending a text message to a stranger. A quick “write me a literature review” gets you about as far as “food please” gets you in a restaurant. Your AI assistant needs context—rich, specific, carefully crafted context.
Start with a clear frame. Tell the AI who you are, what you’re working on, and what you need. Plant the seed, and watch the garden grow. Give it boundaries, expectations, and examples. It’s not unlike showing a research scholar their first steps. The more specific you are, the better your results.
Tools serve you
Or you end up serving tools. Not every AI fits every task. Claude 3.5 Sonnet shines at complex analysis. GitHub Copilot accelerates coding. HeyGen helps create educational videos. Pick your tool like you’d pick your research method—match it to your objective. We discussed this at length in our webinar.
Start small. Small steps make great journeys, but great journeys also begin with the smallest of steps. Test different tools on manageable tasks. Compare their outputs. Build your toolkit gradually, and you’ll develop an instinct for which assistant suits which job. Shop for AI tools like you’re casting characters for another ‘The Office’ reboot.
Frame with precision. Frame with intent.
Frame with clarity. Prompts work best when they follow a clear structure. Here's my tested approach:
* Set the stage with context
* Define the specific task
* Provide examples of what you want
* Specify format and length
* Ask for step-by-step reasoning
* Request specific frameworks or approaches
Think of it as writing a detailed research proposal. Format those citations while you’re juggling flaming chainsaws, APA style. The clearer your requirements, the better your results.
Build better conversations
Stop treating AI like a vending machine. Single-shot prompts rarely give you the best results. Instead, build a conversation. Start broad, then narrow down. Ask follow-up questions. Challenge assumptions. Guide the AI toward your goal through dialogue.
These tools predict text based on patterns. Help them understand your patterns through clear, structured conversation.
Need more guidance? Check out our webinar. We discuss practical applications of AI tools in academic work.
Until next time.
Welcome to episode 2 of the AI Academics Podcast. In this episode, we discuss the latest AI tools that can significantly enhance your academic workflow. We discuss ten reliable AI tools and their practical applications in academia. Additionally, we explore the emerging issue of AI clones and deepfakes, sharing a real-life example of how someone's identity was misused for propaganda purposes. Join us for an insightful conversation.
Exciting travels aside, we've got two major points to cover today. We’ll talk about ten reliable AI tools that can enhance your academic workflow, plus dive into a serious discussion about AI clones. Yes, AI clones are real, and one researcher found herself cloned for purposes she never agreed to.
Breaking Down the Tool List
Here’s a tool list that I tweeted recently. These aren’t sponsored picks—just my personal favourites. Let’s run through them, starting with TypingMind:
TypingMind
This AI user interface (UI) emerged as a favourite of mine, offering a smooth UI to access major APIs like GPT, Gemini, and Claude. The ability to install local versions, like LLaMa or Mistral, on your computer makes it a must-have for academics looking to improve their workflows.
Consensus
Perfect for initial literature searches, Consensus gives quick summaries and references, making it ideal for kick-starting any research project. Yes, Vugar (video) and I have both done detailed reviews on it, so check those out!
Jenni AI
Jenni AI stands out as a co-writing assistant. It had a steep learning curve, but once you get used to it, the tool can be a great companion. It’s perfect for breaking the blank page syndrome and offers a conversation-like interface to help you develop your writing.
PaperPal
PaperPal comes in handy when working in Word. It offers paraphrasing options and gives writing suggestions that can make your work more fluid and concise. It's a lifesaver when dealing with Word documents.
Writefull
If you’re working in LaTeX and using Overleaf, Writeful is your go-to tool. It suggests edits on the go and integrates seamlessly with your writing flow. It helps you maintain clarity and coherence, making academic writing less of a chore.
Otter.ai
Otter.ai isn’t just for meeting transcriptions. With its Otter Bot feature, you can chat with your transcripts, making it perfect for lectures and notes review.
SciteAI
Vugar’s favourite, SciteAI, brings smart citations and writing assistance to the foreground. It even narrows down sources into supporting, contrasting, or just mentioning—adding an extra layer of refinement to your research.
Perplexity
For those simple queries that need a refined touch, Perplexity replaces Google for many, giving AI-generated responses that are detailed and insightful.
Speechify
While I have reservations about its pricing, Speechify's text-to-speech feature in your own voice is unique and adds fun to academic reading.
AI Clones: A Growing Concern
The spotlight today also falls on a viral phenomenon. Imagine waking up one day to find your face and voice cloned for purposes you never intended. That's exactly what happened to creator Olga Loiek who woke up to find her likeness used for propaganda in China. Scary, right? This sheds light on the darker side of AI. It shows us how important it is to build AI tools responsibly. Tools like 11Elevenlabs and HeyGen already allow making perfect voice and face clones, but do so with your consent.
Next week, our online thesis workshop aims to help people get unstuck with thesis writing. Run together with Ali Hindi, this session is packed with useful tips for anyone working on a thesis. Get the recording if you missed it.
Final Thoughts
We hope you found value in today's mini AI tools webinar. Follow us on X, LinkedIn, YouTube, or Medium. The AI Academics Podcast is also on Substack. Don’t miss rating us on Apple Podcasts, Spotify, or YouTube. A little love goes a long way.
We’re taking a short break next week, but don’t worry—Vugar and I will be back with more AI insights. Until then, keep geeking out with the best AI tools that matter to your academic life.
Thank you for joining us today. Enjoy your summer, and we’ll see you in the next session!
Say Thanks
💙 Leave a review of the show on Apple Podcasts.
💚 Leave a rating of the show on Spotify.
In this episode of the AI Academics podcast, hosts Dr. Lennart Nacke and Vugar Ibrahimov discuss the recent Apple announcement about 'Apple Intelligence' and its implications for AI integration into Apple's ecosystem, emphasizing privacy and the cooperation with OpenAI's ChatGPT. The conversation covers the advancements in tools for academics, ethical implications of AI, and how AI can be used to improve workflow while maintaining the human element in critical thinking and decision-making processes. The episode also explores how AI could reshape academic research and the importance of understanding which tasks should be delegated to AI. Live audience questions are addressed as well.
Timestamps:
00:00 Introduction to the AI Academics Podcast
00:27 Going Live: New Platforms and Venues
01:21 Apple Intelligence Announcement
06:49 Privacy Concerns and AI Integration
12:54 AI Tools for Academics
22:15 Pushback on AI Tools in Academia
23:12 Critical Thinking vs. AI Assistance
25:46 Integrating AI in Education
28:04 Ethical and Practical Considerations of AI
31:00 Environmental Impact of AI
33:47 Coding in the Age of AI
38:44 The Future of AI and Human Tasks
41:29 Q&A and Final Thoughts
WHEN YOU'RE READY
📮 Write Insight Newsletter: https://go.lennartnacke.com/newsletter
🤖 Get the AI Tools Webinar Recording: https://go.lennartnacke.com/aitoolswebinar
🧞♂️ Book a seminar from us
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CONNECT
𝑿 Connect on X: @acagamic & @vugar_ibrahimov
🧢 Connect on LinkedIn: Lennart Nacke & Vugar Ibrahimov
📰 Subscribe on Medium: @acagamic & @vugar_ibrahimov
🔴 Subscribe on YouTube: @acagamic & @vugar_ibrahimov
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SAY THANKS
💙 Leave a review of the show on Apple Podcasts
💚 Leave a rating of the show on Spotify
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