top of page

Critical AI Literacy

Empowering Everyday Professionals for the AI Era

July 28 - August 15

ai-cloud-concept-with-robot-arms.jpg
Course 
Weekly
Schedule
Tuesday
Live Lab
11:00am - 12:15pm EST
Thursday
Live Lab
11:00am - 12:15pm EST
Friday
Demo Day
11:00am - 1:00pm EST

What Is Critical AI Literacy?

AI is reshaping how we work, learn, and make decisions — but most people using AI today are doing so without the tools to understand, question, or improve it.

​

At SeqHub, we believe AI shouldn’t be a black box. Our Critical AI Literacy initiative empowers entry-level professionals from all backgrounds to become confident, responsible collaborators with AI tools — not just passive users.

 Why It Matters

Whether you're starting a career in healthcare, logistics, creative work, or customer support, you’re already encountering AI — in search, forms, assistants, or scheduling tools.

But AI isn't neutral.

It can be:

  • Biased by the data it learns from

  • Overconfident, even when wrong

  • Easily manipulated by the way we prompt it

  • Prone to sycophancy — telling us what it thinks we want to hear

 

That’s why we teach people to not only use AI — but to understand how it works, when to trust it, and how to use it to improve real-world work.

 The Critical AI Literacy Program

Our learning experience is guided by a simple, research-informed model: Look → Think → Do
LOOK:
Learn how AI systems
function and fail
THINK:
Reflect on how AI affects
real-world decisions
DO:
Build simple, useful AI tools and workflows, without code

This program is designed for:

Entry-level professionals and workforce
re-trainers
Learners with no technical background
Organizations preparing staff for AI-enhanced work
Anyone who wants to be AI-aware, not
AI-replaced

What Makes This Different?

Look-Think-Do AI Co-Teacher

Every learner is supported by an adaptive AI guide that explains, prompts reflection, and offers feedback throughout the course.

Live + Asynchronous Learning

A flexible structure balances live instruction with self-paced LTD (Look–Think–Do) sessions, making it accessible for varied schedules.

Project-Based

Each week culminates in a tangible AI-powered artifact, from custom assistants to verification workflows shared during Demo Day presentations.

Field-Agnostic

Designed to be relevant across industries, including healthcare, logistics, creative work, administration, and more.

Real AI Tools, No Code Needed

  •  Learners get hands-on experience with:

    • Lovable (no-code AI agent builder)

    • NotebookLM (AI-powered document researcher)

    • Gemini Advanced (deep research + prompt engineering)

Topics You Will Cover

  • Understand how large language models (LLMs) generate answers and why they sometimes sound confident but get things wrong.

  • Learn how to ask questions that help AI respond more accurately, and avoid vague or misleading answers.

  • Practice recognizing when AI is making things up, showing bias, or just telling you what it thinks you want to hear (also called sycophancy).

  • Apply AI to real work; like writing summaries, checking instructions, or helping with step-by-step procedures.

  • Build your own simple AI helpers using tools like Lovable, NotebookLM, and Gemini — no programming experience needed.

Course Overview
Week 1: AI Fundamentals & Critical Understanding

    • Understanding how large language models work through accessible analogies

    • Exploring AI applications in documentation, calculations, and procedures

    • Hands-on practice with effective prompting for workplace tasks

    • Introduction to the specialized AI assistant project

    • Biotech Focus: Examples and exercises specific to laboratory documentation

    • Creating clear templates for procedure write-ups and record-keeping

    • Learning communication strategies for consistent documentation

    • Developing personalized documentation templates for professional use

    • Practical application of prompting principles

    • Biotech Focus: Laboratory notebook formats and procedural documentation

    • Understanding why AI makes mistakes in professional contexts

    • Identifying potentially dangerous hallucinations in procedures

    • Recognizing biased responses that could affect work outcomes

    • Developing verification strategies for critical information

    • Biotech Focus: Safety-critical laboratory procedures and protocols

    • Building personal verification checklists for AI-generated content

    • Analyzing case studies of AI errors in professional settings

    • Creating systematic approaches to validating AI outputs

    • Implementing verification strategies for critical procedures

    • Biotech Focus: Laboratory safety verification and protocol validation

    • Student presentations of specialized AI assistants for workplace tasks

    • Peer feedback and improvement strategies

    • Discussion of verification approaches and best practices

    • Awards for most innovative and most practical assistants

    • Biotech Focus: Laboratory-specific assistant applications

Week 2: Practical Tools & Critical Evaluation

    • Introduction to accessible AI tools for organizing workplace information

    • Using AI assistants to create and manage documentation templates

    • Verifying procedures using available reference sources

    • Hands-on practice with creating AI-assisted documentation systems

    • Biotech Focus: Laboratory procedure organization and reference systems

    • Creating organized systems for procedures and references

    • Using AI to develop searchable documentation libraries

    • Building verification strategies into documentation workflows

    • Planning effective information management systems

    • Biotech Focus: Laboratory protocol management and accessibility

    • Understanding how bias affects procedure recommendations

    • Testing how different phrasings affect AI safety recommendations

    • Identifying when AI prioritizes user preferences over established protocols

    • Developing strategies to ensure consistent, protocol-aligned information

    • Biotech Focus: Laboratory safety procedures and regulatory compliance

    • Conducting experiments comparing AI responses to different scenarios

    • Creating systems to identify potentially biased recommendations

    • Developing frameworks for consistent, protocol-aligned AI use

    • Building bias detection tools for workplace applications

    • Biotech Focus: Laboratory procedure consistency and safety standards

    • Student presentations of workplace information management systems

    • Demonstrations of bias detection strategies for professional contexts

    • Group discussion on practical applications

    • Recognition of most effective implementations

    • Biotech Focus: Laboratory information management applications

Week 3: Building Practical AI Applications

    • Building custom AI applications without coding skills

    • Security and privacy considerations for sensitive data

    • Starting development of practical workplace assistant applications

    • Understanding AI integration for professional tools

    • Biotech Focus: Laboratory-specific applications and data considerations

    • Step-by-step creation of AI tools for workplace tasks

    • Implementation of verification and bias detection features

    • Testing applications with realistic scenarios

    • Iterative improvement based on testing results

    • Biotech Focus: Laboratory procedure assistants and calculation tools

    • Enhancing applications with security safeguards

    • Peer testing and feedback

    • Addressing edge cases and potential failures

    • Preparing for final demonstrations

    • Biotech Focus: Laboratory safety considerations and edge cases

    • Finalizing applications for presentation

    • Creating documentation of development process

    • Preparing presentation materials highlighting critical thinking

    • Developing deployment plans for workplace settings

    • Biotech Focus: Laboratory implementation considerations

    • Student presentations of completed AI applications

    • Discussion of real-world applications in professional settings

    • Certificate ceremony and celebration

    • Next steps for continued AI literacy development

    • Biotech Focus: Laboratory innovation showcase and implementation planning

BioLaunch Standard Alignment

This program directly supports key BioLaunch standards:

    • AI-assisted laboratory notebook documentation

    • Optimized sample tracking and inventory systems

    • Standardized reporting formats for consistent documentation

    • AI tools for drafting and refining Standard Operating Procedures

    • Verification systems for procedure accuracy

    • Customized SOP templates for common lab techniques

    • AI applications for solution preparation calculations

    • Automated verification of dilution calculations

    • Tools for double-checking complex laboratory math

    • AI-assisted analysis of spectrophotometry data

    • Protein quantification and experimental results interpretation

    • Maintaining GLP standards with AI verification

    • Critical thinking skills for evaluating information

    • Digital literacy relevant to modern laboratories

    • Portfolio-building for enhanced career opportunities

bottom of page