Human Judgment in the Age of AI & Algorithms (2026) by Zubin Rashid

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Human Judgment in the Age of AI & Algorithms (2026) by Zubin Rashid
Published 10/2026
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 1h 37m | Size: 1.42 GB

A leadership course on knowing when to trust the data, when to trust your gut, and when to do both.

What you'll learn
Identify where algorithms, scores, and AI recommendations already shape decisions on your team
Recognize automation bias and stop deferring to a tool without questioning it
Spot confirmation, anchoring, and overconfidence bias in your own decisions
Explain when human judgment outperforms an algorithm, and when it does not
Use the Trust Calibration Model to decide how much weight a recommendation deserves
Place any decision in one of four zones: Automate, Augment, Advise, or Author
Coach your team to question algorithmic recommendations with confidence and clear reasoning
Design human-in-the-loop checkpoints and ethical guardrails that keep accountability with people

Requirements
No technical, coding, or data science background is needed. Every concept is explained in plain language.
No experience with AI tools is required. If you have ever used a score, ranking, dashboard, or software recommendation at work, you already have enough context.
Any word processor, such as Microsoft Word or Google Docs, to complete the downloadable worksheets.
Optional: a real decision from your own work to practice on. If you do not have one, the examples in the course are enough.
A willingness to try the short role plays and the 30-day audit. They are where the lessons turn into habits.

Description
AI tools now score candidates, rank claims, flag risks, and recommend prices, often before a human has looked at the case. The danger is not that these tools are wrong. It is that they are right often enough that people stop asking questions, and accountability quietly moves to a dashboard nobody can explain.

This course gives leaders a practical way to stay in charge. You will learn when to trust an algorithm, when to question it, and when to override it, using a simple framework you can apply to a real decision the same day.

What you will be able to do
- Spot where algorithms already shape decisions on your team

- Recognize automation bias and the cognitive biases that distort your own judgment

- Explain when human judgment beats an algorithm, and when it does not

- Use the Trust Calibration Model to decide how much weight a recommendation deserves

- Place any decision in one of four zones: Automate, Augment, Advise, or Author

- Coach your team to question recommendations with confidence

- Design human-in-the-loop checkpoints and ethical guardrails that keep accountability with people

What is inside
Short video lessons built around real situations, from hiring and lending to retail pricing and healthcare. After each section, you practice what you learned through graded role plays, such as defending a gut call to a data-driven boss or presenting an overridden decision to your board. You also get downloadable worksheets and short readings, including sample policy language you can adapt. You finish with a 30-day judgment audit that turns the ideas into habits.

Who this course is for
Managers, senior leaders, HR and L&D professionals, and aspiring leaders in any industry. No technical background and no coding are required. If you rely on dashboards, scores, or AI recommendations to make decisions about people, money, or customers, this course is for you.

The machine advises. You decide. This course shows you how to make that true in practice.

Who this course is for
Managers and team leaders who use dashboards, scores, or AI recommendations to make decisions about people, money, or customers
Senior leaders and executives who are accountable for decisions that algorithms now help shape
HR, Talent Acquisition, and L&D professionals who use screening, scoring, or analytics tools and want to use them responsibly
Operations, finance, retail, and customer service leaders who rely on automated forecasts, pricing, or risk flags
Aspiring managers and high-potential employees who want to build sound judgment before they lead a team
Professionals in risk, compliance, and governance who need practical ways to keep a human accountable for automated decisions
This course is not for data scientists or engineers who want to build or train AI models. It focuses on how to use and oversee AI recommendations, not how to create them.

Homepage

Code:

https://rapidgator.net/file/e6318d69ba6c925d8b6f2a84aa759914/Human_Judgment_in_the_Age_of_AI_&_Algorithms.part2.rar.html
https://rapidgator.net/file/943204b5ec530518ef347eba30aefb27/Human_Judgment_in_the_Age_of_AI_&_Algorithms.part1.rar.html