Table of contents
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1. Introduction
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1.1. AI in the Legal Domain and the Expanding Use of Algorithmic Decision Making
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1.2. The Need for More Algorithmic Transparency
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1.3. The Opacity of Algorithmic-Decision-Making Software
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1.4. The Role of Explanations within a Complex Process
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2. A Framework for Explanation and Interpretation
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2.1. Trying to Capture the Essence of Explainability
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2.2. Expanding Comparability Dimensions of Machine Learning Algorithms for ADM
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2.3. Explainability as an Intrinsic Property of Machine Learning Algorithms
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3. Conclusion
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4. References