Questions tagged [explainable-ai]

For questions related to explainable artificial intelligence (XAI), also known as interpretable AI, which refers to AI techniques that can be trusted and easily understood by humans, which are particularly relevant in areas like healthcare or self-driving cars. There are several concepts related to XAI, such as accountability, fairness, and transparency.

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74 views

What exactly is an interpretable machine learning model?

From this page in Interpretable-ml book and this article on Analytics Vidhya, it means to know what has happened inside an ML model to arrive at the result/prediction/conclusion. In linear regression, ...
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0answers
25 views

Black Box Explanations: Using LIME and SHAP in python

Recently I came along the paper Robust and Stable Black Box Explanations, which discusses a nice framework for global model-agnostic explanations. I was thinking to recreate the experiments performed ...
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1answer
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What do the notations $\sim$ and $\Delta (A) $ mean in the paper “Fairness Through Awareness”?

In this paper Fairness Through Awareness, the notation $\mathbb{E}_{x \sim V} \mathbb{E}_{a \sim \mu_x} L(x,a)$ is being used (page 5 top line), where $V$ denotes the set of individuals (so I guess ...
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0answers
51 views

Is it possible to create a fair machine learning system?

I started thinking about the fairness of machine learning models recently. Wiki page for Fairness_(machine_learning) defines fairness as: In machine learning, a given algorithm is said to be fair, ...
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2answers
32 views

Can a NN be configured to indicate which points of the input influenced its prediction and how?

Suppose I want to classify a dataset like the MNIST handwritten dataset, but it has added distractions. For example, here we have a 6 but with extra strokes around it that don't add value. I suppose ...
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0answers
129 views

Has anyone attempted to take a bunch of similar neural networks to extract general formulae about the focus area? [closed]

When a neural network learns something from a data set, we are left with a bunch of weights which represent some approximation of knowledge about the world. Although different data sets or even ...
3
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1answer
91 views

What needs to be done to make a fair algorithm?

What needs to be done to make a fair algorithm (supervised and unsupervised)? In this context, there is no consensus on the definition of fairness, so you can use the definition you find most ...
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3answers
147 views

Who is working on explaining the knowledge encoded into machine learning models?

The thing about machine learning (ML) that worries me is that "knowledge" acquired in ML is hidden: we usually can't explain the criteria or methods used by the machine to provide an answer ...
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8answers
10k views

Why do we need explainable AI?

If the original purpose for developing AI was to help humans in some tasks and that purpose still holds, why should we care about its explainability? For example, in deep learning, as long as the ...
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1answer
152 views

Is tabular Q-learning considered interpretable?

I am working on a research project in a domain where other related works have always resorted to deep Q-learning. The motivation of my research stems from the fact that the domain has an inherent ...
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1answer
59 views

Is explainable AI more feasible through symbolic AI or soft computing?

Is explainable AI more feasible through symbolic AI or soft computing? How much each paradigm, symbolic AI and soft computing (or hydrid approaches), adresses explanation and argumentation, where ...
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2answers
217 views

Which explainable artificial intelligence techniques are there?

Explainable artificial intelligence (XAI) is concerned with the development of techniques that can enhance the interpretability, accountability and transparency of artificial intelligence and, in ...
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0answers
113 views

How can we create eXplainable Artificial Intelligence?

Currently, we can build the Artificial Intelligence (AI) approaches that respectively explain their actions within the use of goal trees 1. By moving up and down across the tree, it keeps tracking the ...
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2answers
324 views

How is the “right to explanation” reasonable?

There has been recent uptick in interest in eXplainable Artificial Intelligence (XAI). Here is XAI's mission as stated on its DARPA page: The Explainable AI (XAI) program aims to create a suite of ...
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1answer
221 views

How would one debug, understand or fix the outcome of a neural network?

It seems fairly uncontroversial to say that NN based approaches are becoming quite powerful tools in many AI areas - whether recognising and decomposing images (faces at a border, street scenes in ...
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8answers
14k views

Do scientists know what is happening inside artificial neural networks?

Do scientists or research experts know from the kitchen what is happening inside complex "deep" neural network with at least millions of connections firing at an instant? Do they understand the ...