Get to know how AI learns

I heard AI described as “augmented human intelligence” and believe it is an insightful way to characterize this new technology and its role in various applications. AI systems are designed to complement and enhance human capabilities rather than replace them entirely. They can process vast amounts of data, make predictions, and assist with decision-making, ultimately extending and amplifying human intelligence and productivity.

As you research AI tools and your current HR vendors begin to add AI to their offerings, you will need to become familiar with how AI learns and the associated risks so you can ask critical questions before you begin to use AI-related systems. Here are a couple of AI learning methods and their benefits and risks.

Machine Learning

Benefits

• Adaptability: Machine learning models can adapt to new data, making them versatile in a wide range of applications.

• Automation: Machine learning can automate complex tasks, making it efficient and cost-effective.

• Data-driven insights: Machine learning extracts valuable insights from large datasets for better decision-making.

Risks

• Bias: Models can inherit biases from training data, leading to unfair or discriminatory results.

• Lack of transparency: Some machine learning models are black boxes, making it hard to explain their decisions.

• Data dependence: Machine learning models rely heavily on the quality and quantity of training data.

Rule-Based Systems

Benefits

• Explicit control: Rules are explicitly defined, offering control and predictability.

• Domain specificity: Rule-based systems are effective for well-defined domains with clear rules and regulations.

Risks

• Limited adaptability: Rule-based systems may struggle with handling ambiguous or evolving situations.

• Maintenance overhead: Updating rules can be labor-intensive as systems need manual adjustments.

Reinforcement Learning

Benefits

• Autonomous learning: Ability to learn through interaction and adapt without explicit programming.

• Suitable for dynamic environments: Effective in environments with changing conditions.

Risks

• Exploration challenges: Learning through trial and error can be time-consuming and inefficient.

• Safety concerns: Risky actions might be taken before optimal strategies are discovered.

Next, in this ongoing series on AI and HR, we’ll delve into questions to ask your vendors as you explore tools and solutions. In the meantime, if you’d like to check out the other posts in the series, click here.