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Explainability in AI and Machine Learning Systems: An Overview

Heartbeat

Source: ResearchGate Explainability refers to the ability to understand and evaluate the decisions and reasoning underlying the predictions from AI models (Castillo, 2021). Explainability techniques aim to reveal the inner workings of AI systems by offering insights into their predictions. What is Explainability?

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xECGArch: A Multi-Scale Convolutional Neural Network CNN for Accurate and Interpretable Atrial Fibrillation Detection in ECG Analysis

Marktechpost

Explainable AI (xAI) methods, such as saliency maps and attention mechanisms, attempt to clarify these models by highlighting key ECG features. The study utilized four extensive 12-lead ECG databases: PTB-XL, Georgia-12-Lead, China Physiological Signal Challenge 2018 (CPSC2018), and Chapman-Shaoxing, all sampled at 500 Hz.

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4 Key Risks of Implementing AI: Real-Life Examples & Solutions

Dlabs.ai

The International Data Corporation predicts that the global datasphere will swell from 33 zettabytes in 2018 to a staggering 175 zettabytes by 2025. Possible solution: Explainable AI Fortunately, a promising solution exists in the form of Explainable AI.

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13 Biggest AI Failures: A Look at the Pitfalls of Artificial Intelligence

Pickl AI

Example In 2018, a self-driving car developed by Uber struck and killed a pedestrian in Arizona. Privacy Concerns As AI systems become more sophisticated, they require access to vast amounts of data. This experiment highlighted the importance of developing robust security measures for AI systems.

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AI for Climate Change and Weather Risk

DataRobot Blog

From 2018 to 2020, the U.S. Using either the code-centric DataRobot Core or no-code Graphical User Interface (GUI), both data scientists and non-data scientists such as risk analysts, government experts, or first responders can build, compare, explain, and deploy their own models. The scale and costs of weather disasters in the U.S.

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The History of Artificial Intelligence (AI)

Pickl AI

The future of AI also holds exciting possibilities, including advancements in general Artificial Intelligence (AGI), which aims to create machines capable of understanding and learning any intellectual task that a human can perform. 2004: Discussions about Generative Adversarial Networks (GANs) begin, signalling the start of a new era in AI.

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“Artificial Intelligence Act “— EU attempts to tame the tech dragon

Mlearning.ai

The EU AI Act is a proposed piece of legislation that seeks to regulate the development and deployment of artificial intelligence (AI) systems across the European Union. Photo by Guillaume Périgois on Unsplash EU AI Act: History and Timeline 2018 : EU Commission starts pilot project on ‘Explainable AI’.