EdTech Connect Ep. 73 – Ben Tasker: Living in the AI Between Times

Host: Jeff Dillon
Guest: Ben Tasker
Date: February 6, 2026

Episode Overview

In this thought-provoking episode, Jeff Dillon sits down with Ben Tasker—AI educator, strategist, and leader in large-scale workforce transformation—to discuss the “AI between times,” a transitional era bridging the familiar past and the anticipated “AI future.” Tasker brings a unique perspective from roles spanning higher ed, enterprise, and healthcare, exploring the challenges, opportunities, and transformative potential of AI in learning and work. Expect practical insights for educators, learning leaders, and anyone rethinking readiness for the future.

Key Discussion Points & Insights

Defining the “AI Between Times” (00:00, 03:13)

• Concept: We’re living in a liminal, “funky” period not fully rooted in the old ways of pre-2020, nor fully realized in the AI-driven futures often promised.
• Historical Parallel: Tasker likens this to earlier economic revolutions. “AI is going to have the same impact as all of those transformations… it's actually going to probably happen faster…” (A, 00:00; 03:30)
• Challenges: Rapid transformation, uncertainty over duration, and disruptive “AI oh moments” (unexpected shocks and rapid adjustments).

Early Exposure & Spark for AI (02:02)

• Tasker’s Origin Story: Childhood curiosity led to data science, but first experience of AI was cinematic:
  “My first time interacting with AI… my mother let me watch the first two Terminator movies. That was my first reincarnation of AI and it's kind of stuck with me ever since.” (A, 02:13)
• AI Personas: Noted how both fictional and real AIs have primary objectives.

How Higher Ed Can Rethink Workforce Readiness (06:01–10:28)

• Education Model Flaws: Timelines (4-year degrees) don’t match the pace of AI change.
• Role Shift: With AI, continuous upskilling and micro-credentialing matter more than static degrees.
  “It's not just one and done anymore… upskilling, reskilling was something we kind of talked about, but it wasn't a big initiative…” (A, 06:01)
• SNHU Model: Short, stackable courses with embedded AI tools allow students to accelerate learning and earn micro-credentials, convertible to college credit.
• Workforce Integration: Organizations should use “skills planning” for mapping current and future needs, and foster fast, ongoing skill acquisition.

AI as Augmenter, Not Replacement (10:28)

• Amplification, Not Replacement:
  “AI doesn't replace people, it amplifies what they're capable of.” (B, 10:28)
• Examples: Companies that upskill workers alongside AI see a 52% revenue bump (A, 10:58).
• Trap: Implementing “point solutions" (single-use AI tools) without system-level planning often results in costly missteps or even re-hiring workers previously replaced by automation.

Opportunities and Risks in Education (13:11–16:35)

• Student Vulnerability: K–12 students are at higher risk to AI-driven misinformation or inappropriate guidance.
• Embedding AI Responsibly: Safer, school-provided AI tools with guardrails and monitoring reduce misuse and foster learning.
• Real-World Example:
  “Intro coding students with embedded AI went eight weeks faster and covered more ground than those without… they're not cheating, they're actually trying to learn.” (A, 15:19)

Responsible AI & Ethics—Laying the Foundation (16:48–18:06; 22:00–24:47)

• Start with Responsibility: Before rolling out tech, prioritize frameworks for transparency, fairness, and accountability.
  “We need to be transparent… when we have that AI oh moment, we can go back and think about what went wrong, how we fix it…” (A, 17:01)
• Create Structures: Set up steering committees to guide, review, and adjust AI initiatives.
• Applied AI: Institutions should embed AI across disciplines, not just technical programs, to maximize preparedness.

Shifting from Degree to Skills-Based Learning (18:06–20:02)

• Skills over Seat-Time:
  “A skill is something that you're really good at and that you can perform consistently over time… It's not necessarily about doing four years, but about mastering and proving you can do (the work).” (A, 18:06)
• Mentorship & Adjacency: Learning flows from project-based, real-world collaboration—not just formal coursework.

Success Patterns Across Sectors (20:02–22:00)

• Human-Centered AI: Lasting impact comes when data science solutions are deeply tied to human stories and needs—whether helping cancer patients or at-risk students.
• Unexpected Roles:
  “Usually data science is in a cube… I never thought I was gonna meet a patient, but I did… had to knock some doors to help get some water filtration done.” (A, 20:56)

What’s Next: Trends and Advice (24:47–28:00)

• Most Exciting Trend: AI-enabled, on-demand, personalized education; truly accessible learning for all, no longer limited to formal enrollment.
  “Education is going to become more accessible, not just in-classroom or out… anyone that wants to learn at any time… will be able to.” (A, 25:14)
• Immediate Steps:
  “If you haven't already learned AI… write down what skills you have, what you want to gain… AI can help you define and navigate that path.” (A, 26:44)

Looking to the Future (28:00)

• Skills-Based Learning to the Fore:
  “I'm really hoping that skills based learning, competency based education… becomes much more mainstream. Degrees are becoming too expensive… skills are the way to go.” (A, 28:00)

Notable Quotes & Timestamps

• On Living in Transition:
  “The AI between times is this really funky time period… we’re not really into that AI future yet… but we’re not really out of the past either.” – Ben Tasker (A, 00:00/03:30)

• On Education’s Slow Pace:
  “With AI, time kind of changes… it's not just one and done anymore.” – Ben Tasker (A, 06:01)

• On AI’s True Role:
  “AI doesn't replace people, it amplifies what they're capable of.” – Jeff Dillon paraphrasing Tasker (B, 10:28)

• On Applied AI:
  “Applied AI is just as impactful as the technical AI… how you build a chatbot with a low code, no code tool… it's building responsible and ethical AI into the business.” – Ben Tasker (A, 23:43)

• On Immediate Action:
  “Write down what skills you have, what skills you want to gain… AI can help you define and navigate that path.” – Ben Tasker (A, 26:44)

• On the Future of Learning:
  “Education is going to become more accessible… anyone that wants to learn at any time… will be able to.” – Ben Tasker (A, 25:14)

Suggested Actionable Takeaways

• Start with Ethics: Form a responsible AI committee and set clear guidelines before implementation.
• Embrace Skills Planning: Catalog current and needed skills in your organization; develop rapid, project-based upskilling.
• Embed AI in Learning: Safely integrate AI tools for support and acceleration, with monitoring for responsible use.
• Shift Mindset: Move from “time served” to skills & outcomes, both for personal growth and institutional policy.

Memorable Moments

• Tasker’s first memorable AI was the Terminator films as a child (02:13)
• Case study: Coding course with Claude AI embedded, leading to double the learning pace and deeper engagement (15:19)
• Real-world “AI gone wrong”: Companies prematurely automating jobs, then re-hiring at scale (10:58)
• Story of data science moving out of the back office—Tasker meeting patients while running a public health AI initiative (20:56)

Important Segment Timestamps

• [00:00] – Defining the “AI between times”
• [02:13] – Tasker’s early experiences with AI
• [06:01] – How higher ed can support workforce transformation with AI
• [10:28] – AI as amplifier, not replacement
• [13:23] – Opportunities & risks of AI in education
• [15:19] – Embedded AI in coding courses: real results
• [16:48] – Laying foundations for responsible AI
• [18:06] – Why shift to skills-based learning?
• [20:24] – Success patterns: Human-centered AI
• [22:00] – Embedding responsibility & ethics from the start
• [25:14] – Most exciting trends in AI-backed learning
• [26:44] – One actionable step for this week
• [28:00] – Hopes for the next five years in EdTech

Ben Tasker's journey across higher ed, industry, and healthcare delivers a nuanced portrait of AI’s promise and pitfalls, urging institutions and individuals alike to move boldly—but thoughtfully—through the “AI between times.”