World Congress 2024 β€’ Aug 20, 2024

AI for decision-making in Tech Recruiting

Olena Linnyk

Are your existing job descriptions secretly reinforcing historical hiring biases? Discover how pairing blind AI skill matching with human intuition creates a radically fair tech recruiting funnel.

Pause
Mute Enter Fullscreen
#1 about 2 min

Statistical learning and sequence patterns in artificial brains

Analyzing large datasets identifies frequent sequential text patterns that enable statistical models to learn languages.

#2 about 2 min

Correlation patterns and attention mechanisms in language models

Attention mechanisms allow models to capture correlating patterns over longer distances and understand contextual word meaning.

#3 about 2 min

Advantages and data requirements of statistical AI learning

Artificial intelligence rapidly processes tremendous amounts of data but requires highly balanced datasets to mitigate bias.

#4 about 2 min

Generalization and idealistic learning in human cognition

Humans learn through idealization and generalization, allowing effective decision-making from very few real-world examples.

#5 about 2 min

Cognitive bias and correlation traps in human decision-making

Generalization in human thinking often leads to subconscious bias by confusing mere correlation with true causation.

#6 about 2 min

Neurological differences between artificial neural networks and brains

The human brain utilizes recurrent closed loops for long-term memory, unlike simple feedforward artificial neural networks.

#7 about 3 min

Measuring and mitigating gender bias in job advertisements

Analytical tools identify and correct male-coded language in job postings to attract more diverse candidate pools.

#8 about 3 min

Ensuring transparency and fairness in AI matching systems

Constraining algorithmic data access allows candidate matching systems to evaluate applications on skills rather than demographic traits.

#9 about 2 min

Collaborating with AI to handle transformative edge cases

Human intervention remains absolutely necessary when data is scarce or unprecedented shifts render historical models entirely useless.

#10 about 2 min

Anonymizing demographic data for fair skill-based candidate ranking

Parsing resumes to completely anonymize demographics ensures candidate ranking algorithms base decisions solely on weighted skills.

#11 about 3 min

Navigating AI-generated candidate resumes and skill verification

As candidate applications become highly optimized by generation tools, verified credentials and automated agent screening become vital.

Matching moments

1:28 min

Applying AI into the daily recruitment process

JosΓ© Kadlec JosΓ© Kadlec Β· WWC 2025

4:47 min

Navigating AI bias and maintaining human connection

Rudi Bauer Rudi Bauer +1 Β· Cappuccino with HR

3:21 min

Strategies for implementing artificial intelligence in human resources

Rudi Bauer Rudi Bauer +1 Β· Cappuccino with HR

6:47 min

Evaluating artificial intelligence adoption and competence in recruiting

Rudi Bauer Rudi Bauer +1 Β· Cappuccino with HR

3:26 min

Strategies for adapting talent acquisition to AI landscapes

Robindro Ullah Robindro Ullah Β· WWC Europe 2026

4:14 min

Examining AI recruitment implementations in major talent platforms

Malcolm Myers Malcolm Myers Β· WWC 2024

Upcoming sessions on this topic

Open session

World Congress 2026 North America

Beyond the Code: Human-AI Synergies in Product Development

Ajita Kanchivakam Ananth

Staff Technical Program Manager at Google

Ajita Kanchivakam Ananth
Open session

World Congress 2026 North America

AI ROI: The Hard Unit Economics of AI-Native Engineering

Manu Gurudatha

Manu Gurudatha, VP of Engineering at PagerDuty

Manu Gurudatha
Open session

World Congress 2026 North America

The Broken Rung: How AI is Rebuilding Software Development from the Ground Up

Tomislav Tipurić

Chief Technology Officer, Nephos

Tomislav Tipurić
Open session

World Congress 2026 North America

Engineering the Pivot: How Creative Strategy Solves the Hard Problems of AI Accuracy and Scale

Shruti Tiwari

AI/ML product manager, Dell

Shruti Tiwari
Open session

World Congress 2026 North America

Who Tests the AI? Building Trustworthy AI Systems at Enterprise Scale

Him Raj Singh

PayPal, Manager, Software Engineer

Him Raj Singh
Open session

World Congress 2026 North America

Building Pragmatic AI: 10 AI Features Your Users Actually Want

Jonathan "J." Tower

.NET Foundation Board | 12x Microsoft MVP | Founder & Consultant

Jonathan "J." Tower