article thumbnail

Explainable AI Using Expressive Boolean Formulas

Unite.AI

While AI exists to simplify and/or accelerate decision-making or workflows, the methodology for doing so is often extremely complex. Indeed, some “black box” machine learning algorithms are so intricate and multifaceted that they can defy simple explanation, even by the computer scientists who created them.

article thumbnail

What are Explainability AI Techniques? Why do We Need it?

Analytics Vidhya

The quality of AI is what matters most and is one of the vital causes of the failure of any business or organization. According to a survey or study, AI […] The post What are Explainability AI Techniques? Why do We Need it? appeared first on Analytics Vidhya.

professionals

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

Adding Explainability to Clustering

Analytics Vidhya

Introduction The ability to explain decisions is increasingly becoming important across businesses. Explainable AI is no longer just an optional add-on when using ML algorithms for corporate decision making. While there are a lot of techniques that have been developed for supervised algorithms, […].

article thumbnail

Global executives and AI strategy for HR: How to tackle bias in algorithmic AI

IBM Journey to AI blog

The new rules, which passed in December 2021 with enforcement , will require organizations that use algorithmic HR tools to conduct a yearly bias audit. This means that processes utilizing algorithmic AI and automation should be carefully scrutinized and tested for impact according to the specific regulations in each state, city, or locality.

article thumbnail

How Large Language Models Are Unveiling the Mystery of ‘Blackbox’ AI

Unite.AI

Thats why explainability is such a key issue. People want to know how AI systems work, why they make certain decisions, and what data they use. The more we can explain AI, the easier it is to trust and use it. Large Language Models (LLMs) are changing how we interact with AI. Lets dive into how theyre doing this.

article thumbnail

Opening the black box: how ‘explainable AI’ can help us understand how algorithms work

Flipboard

When you visit a hospital, artificial intelligence (AI) models can assist doctors by analysing medical images or predicting patient outcomes based on …

article thumbnail

Top 10 Explainable AI (XAI) Frameworks

Marktechpost

To ensure practicality, interpretable AI systems must offer insights into model mechanisms, visualize discrimination rules, or identify factors that could perturb the model. Explainable AI (XAI) aims to balance model explainability with high learning performance, fostering human understanding, trust, and effective management of AI partners.