DeepAI AI Chat
Log In Sign Up

Explaining Explanations in AI

by   Brent Mittelstadt, et al.

Recent work on interpretability in machine learning and AI has focused on the building of simplified models that approximate the true criteria used to make decisions. These models are a useful pedagogical device for teaching trained professionals how to predict what decisions will be made by the complex system, and most importantly how the system might break. However, when considering any such model it's important to remember Box's maxim that "All models are wrong but some are useful." We focus on the distinction between these models and explanations in philosophy and sociology. These models can be understood as a "do it yourself kit" for explanations, allowing a practitioner to directly answer "what if questions" or generate contrastive explanations without external assistance. Although a valuable ability, giving these models as explanations appears more difficult than necessary, and other forms of explanation may not have the same trade-offs. We contrast the different schools of thought on what makes an explanation, and suggest that machine learning might benefit from viewing the problem more broadly.


page 1

page 2

page 3

page 4


Efficient computation of contrastive explanations

With the increasing deployment of machine learning systems in practice, ...

Explaining Explanations to Society

There is a disconnect between explanatory artificial intelligence (XAI) ...

Explanatory Pluralism in Explainable AI

The increasingly widespread application of AI models motivates increased...

Do People Engage Cognitively with AI? Impact of AI Assistance on Incidental Learning

When people receive advice while making difficult decisions, they often ...

Model Explanations under Calibration

Explaining and interpreting the decisions of recommender systems are bec...

Do not explain without context: addressing the blind spot of model explanations

The increasing number of regulations and expectations of predictive mach...

TED: Teaching AI to Explain its Decisions

Artificial intelligence systems are being increasingly deployed due to t...