Archives for Explainable AI

23 Jan

Council Post: The Fault in AI Predictions: Why Explainability Trumps Predictions

Vinay Kumar Sankarapu explainability and interpretability aren't used

While everyone focuses on model manufacturing, the right product teams have started emphasising the fundamentals of good AI Solutions. XAI is the 101 feature to achieve it. However, the vision of achieving trustworthy AI is incomplete without Explainability. The idea that Explainability will provide insights into understanding model behaviours is, however, currently only serving the needs of AI experts.

The post Council Post: The Fault in AI Predictions: Why Explainability Trumps Predictions appeared first on Analytics India Magazine.

11 May

Top GitHub libraries for building explainable AI models

Avi Gopani ai blackbox

Tensorboard’s WhatIf is a screen to analyse the interactions between inference results and data inputs. I

The post Top GitHub libraries for building explainable AI models appeared first on Analytics India Magazine.

23 Apr

How to make text classification explainable with the SS3 classifier?

Sourabh Mehta Classification

SS3 has obtained state-of-the-art performance on the early risk detection (ERD) problems on text streams. Since it was designed to deal with risk detection over text streams, it supports incremental training and classification, as well as a visual explanation

11 Apr

Council Post: Tackling ethical challenges in AI within organisations

Aishwarya Srinivasan accountability

The components of ethical AI should be incorporated from the product development stage.

07 Apr

Council Post: Beyond Explainable AI—How to infuse trust in AI systems

Shashank Shekhar Contract

Contractual trust is a concept that dictates and quantifies trustworthy AI.

06 Apr

Council Post: Does a lack of XAI put AI startups at risk of failing?

Anirban Nandi ai startups

Instinct is a marvellous thing. It can neither be explained nor ignored ― Agatha Christie.

24 Mar

A guide to XAutoML: A tool for visual analytics

Waqqas Ansari analytics tools

XAutoML is an analytics tool that explains the AutoML optimization procedures and machine learning pipelines constructed by AutoML.

20 Feb

A guide to Quantus: an explainable AI toolkit

Vijaysinh Lendave AI

Explainable AI refers to strategies and procedures used in the application of artificial intelligence (AI) that allow human specialists to understand the solution's findings.

16 Feb

Council Post: Explainable AI and its impact on creating a data-driven culture

Anirban Nandi AI accountability

Explainable AI (XAI) aims to address how black box decisions of AI systems are made.

11 Feb

Explainable AI’s disagreement problem

Shraddha Goled AI Black Box

Critics have often spoken about the ambiguous nature of the term ‘explainability’, going as far as calling it virtual signalling that is severely disconnected from reality.

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