Pipeline CEO Takes On the Gender Equity Gap

Pipeline CEO Takes On the Gender Equity Gap

Assessment

Interactive Video

Business

University

Hard

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The video discusses unconscious bias in HR decisions, focusing on gender equity. It highlights the use of data and algorithms to improve HR decisions across hiring, pay, performance, potential, and promotion. The target audience is large companies committed to gender equity. Research shows a link between gender equity and increased revenue. Challenges in internal mobility for women are explored, and platform solutions are provided. The impact of social movements like Me Too is discussed, along with concerns about AI and unconscious bias.

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5 questions

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1.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What are the five pillars of talent that the company focuses on to address unconscious bias?

Hiring, pay, performance, potential, and promotion

Recruitment, training, development, retention, and succession

Selection, salary, appraisal, growth, and recognition

Onboarding, compensation, evaluation, advancement, and diversity

2.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

According to the research study, what is the revenue increase associated with a 10% rise in gender equity?

1 to 2% increase

3 to 4% increase

5 to 6% increase

7 to 8% increase

3.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is one of the main challenges companies face in promoting gender equity?

Insufficient training programs for women

Women not being promoted at the same rate as men

Lack of qualified female candidates

High turnover rates among female employees

4.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

How does the platform assist companies in making pay decisions?

By negotiating salaries on behalf of employees

By informing them of unconscious bias in pay decisions

By offering payroll management software

By providing salary benchmarks

5.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is a major concern in the research community regarding AI and unconscious bias?

Unconscious bias may be programmed into AI algorithms

AI lacks the ability to learn from human behavior

AI cannot process large datasets

AI is too expensive to implement