Kevin D. Ashley

Books

• Artificial Intelligence and Legal Analytics: New Tools for Law Practice in the Digital Age, Kevin D. Ashley, Cambridge University Press (2017).
• Legal Knowledge and Information Systems, Jurix 2013: The Twenty-Sixth Annual Conference. Kevin D. Ashley (Ed.) IOS Press. Amsterdam (2013).
• Aleven, V., Ashley, K., Lynch, C., & Pinkwart, N. (Eds.), Proceedings of the Workshop on Intelligent Tutoring Systems for Ill-Defined Domains at the 9th International Conference on Intelligent Tutoring Systems. (2008). Montreal, Canada. 
• Kevin D. Ashley, M. Ikeda & T-W Chan (eds.), Intelligent Tutoring Systems. Proceedings from 8th International Conference, ITS 2006 Taiwan (Springer June 2006).
• Kevin D. Ashley & D. G. Bridge (eds.), Case-Based Reasoning Research and Development. Proceedings from 5th International Conference on Case-Based Reasoning (Springer 2003).

Special Issues

• The Journal of Writing Research, Special Issue entitled “Redesigning Peer Review Interactions Using Computer Tools” Schunn, C., Ashley, K. and Goldin, I. (Eds.) 4(2)111-237 (2012).
• International Journal of Artificial Intelligence in Education, Special Issue on AIED applications for ill-defined domains. Pinkwart, N., Lynch, C., Ashley, K. D., & Aleven, V. (Eds.) vol. 19, No. 3 & 4 (2010).
• Journal of Artificial Intelligence and Law, Special Issue on e-Discovery. Ashley, K., Baron, J., and Conrad, J. (Eds.) vol. 18, No. 3 (2010).

Book Chapters
 

• “Mining Information from Statutory Texts: a Case Study” Ashley KD (2021) In: Katz D, Dolin R, and Bommarito M, editors. Legal Informatics. Cambridge University Press: Cambridge, UK.
• “Legal Informatics and the CISG” Ashley, K. in (F. Lachmayer, M. Pavčnik, E. Schweighofer, eds.) Festschrift for Hajime Yoshino. Internationales Rechtsinformatik Symposion (2019).
• “Mining Information from Statutory Texts: a Case Study” Ashley KD (to appear) In: Bommarito M, Dolin R, and Katz D, editors. Legal Informatics. (2019 Forthcoming) Cambridge University Press: Cambridge, UK.
• “Precedent and Analogy” Ashley KD (2018) In: Bongiovanni G, Postema G, Rotolo A, Sartor G, Valentini C, and Walton D, editors. Handbook of Legal Reasoning and Argumentation. Springer: Heidelberg.
• “Evaluating the uses of values in 'A model of legal reasoning with cases incorporating theories and values'” Ashley KD (2013) In: Prakken H, Atkinson K, Wyner A, editors. From Knowledge Representation to Argumentation in AI, Law and Policy Making, A Festschrift in Honour of Trevor Bench-Capon on the Occasion of his 60th Birthday. p. 11-37 College Publications: London.
• “A Survey of Uncertainties and their Consequences in Probabilistic Legal Argumentation,” by M. Grabmair & K. D. Ashley (2012) in (Frank Zenker, ed.) Bayesian Argumentation. pp. 61-86. Springer. Dordrecht.
• "Ill-Defined Domains and Adaptive Tutoring Technologies", Lynch, C., Ashley, K.D., Pinkwart, N., & Aleven, V. (2012). In Durlach, P. & Lesgold, A. M (Eds.), Adaptive Technologies for Training and Education. Cambridge University Press.
• With Lynch, C., Instructional Explanations in a Legal Classroom: Are Students Argument Diagrams of Hypothetical Reasoning Diagnostic?, in Stein, M.K., & Kucan, L. (Eds.) Instructional Explanations in the Disciplines New York: Springer, 2010.
• The Case-Based Reasoning Approach: Ontologies for Analogical Legal Argument, in Approaches to Legal Ontologies, M. Sartor, P. Casanovas, M. Biasotti, and M. Barrera, eds., New York: Springer, 2011.

Articles

• How to improve the explanatory power of an intelligent textbook: a case study in legal writing. Sovrano, F., Ashley, K., Brusilovsky, P. L., & Vitali, F. (2024)  International Journal of Artificial Intelligence in Education, 1-35.
• “Empirical legal analysis simplified: reducing complexity through automatic identification and evaluation of legally relevant factors.” Gray, Morgan A., Jaromir Savelka, Wesley M. Oliver, and Kevin D. Ashley. Philosophical Transactions of the Royal Society A 382, no. 2270 (2024): 20230155.
• “Adding Argumentation into Human Evaluation of Long Document Abstractive Summarization: A Case Study on Legal Opinions.” Elaraby, Mohamed, Huihui Xu, Morgan Gray, Kevin D. Ashley, and Diane Litman. In Proceedings of the Fourth Workshop on Human Evaluation of NLP Systems (HumEval)@ LREC-COLING 2024, pp. 28-35. 2024.
•  “(When) Will Legal Apps Be Able to Read like Lawyers?” K. Ashley, University of California at Los Angeles School of Law, Los Angeles, CA. (In Process).
• “Automatic identification and empirical analysis of legally relevant factors.” Gray, M., Savelka, J., Oliver, W., & Ashley, K. (2023, June). In Proceedings of the Nineteenth International Conference on Artificial Intelligence and Law (pp. 101-110).
• “The unreasonable effectiveness of large language models in zero-shot semantic annotation of legal texts.” Savelka, J., & Ashley, K. D. (2023). Frontiers in Artificial Intelligence, 6.
• “Can GPT Alleviate the Burden of Annotation?” Gray, M., Savelka, J., Oliver, W., & Ashley, K. (2023). In Legal Knowledge and Information Systems (pp. 157-166). IOS Press.
• “Can GPT-4 Support Analysis of Textual Data in Tasks Requiring Highly Specialized Domain Expertise?” Savelka, J., Ashley, K. D., Gray, M. A., Westermann, H., & Xu, H. (2023). Proceedings Sixth Workshop on Automated Semantic Analysis of Information in Legal Text (ASAIL 2023), June, Braga, Portugal. CEUR-WS.org arXiv preprint arXiv:2306.13906.
• “Argumentative segmentation enhancement for legal summarization.” Xu, H., & Ashley, K. (2023) Proceedings Sixth Workshop on Automated Semantic Analysis of Information in Legal Text (ASAIL 2023), June, Braga, Portugal. CEUR-WS.org, arXiv preprint arXiv:2307.05081.
• “Question-Answering Approach to Evaluate Legal Summaries.” Xu, H., and Ashley, K. (2023) Legal Knowledge and Information Systems pp. 293-298 IOS Press.
• “Explaining Legal Concepts with Augmented Large Language Models (GPT-4).” Savelka, J., Ashley, K. D., Gray, M. A., Westermann, H., & Xu, H. (2023). arXiv preprint arXiv:2306.09525.
• “Toward Eliminating Hallucinations: GPT-based Explanatory AI for Intelligent Textbooks and Documentation.” Sovrano, F., Ashley, K., & Bacchelli, A. (2023). In CEUR Workshop Proceedings, no. 3444, pp. 54-65. CEUR-WS, 2023.
• “Pervasive Computational Law.” Guitton, C., Tamò-Larrieux, A., Mayer, S., Ashley, K., Grabmair, M., Sartor, G., ... & van Dijck, G. (2023) IEEE Pervasive Computing, 22(3), 48-51.
• “Toward Automatically Identifying Legally Relevant Factors.” Gray, M., Savelka, J., Oliver, W., and Ashley, K. Legal Knowledge and Information Systems, Jurix 2022, pp. 53-62. IOS Press. Saarbrücken.
• “Multi-granularity Argument Mining in Legal Texts.” Xu, H. and Ashley, K. In Legal Knowledge and Information Systems, Jurix 2022. pp. 261-266. IOS Press. Saarbrücken.
• “Toward an Intelligent Tutoring System for Argument Mining in Legal Texts.” Westermann, H., Šavelka, J., Walker, V.R., Ashley, K.D. and Benyekhlef, K., 2022. In Legal Knowledge and Information Systems (pp. 133-142). IOS Press.
• "On the Role of Past Treatment of Terms from Written Laws in Legal Reasoning." Savelka, J., and K. D. Ashley. New Developments in Legal Reasoning and Logic: From Ancient Law to Modern Legal Systems (2022): 379-395.
• "`Alexa, Write a Memo’: The Promise and Challenges of AI and Legal Writing." Phelps, T., and Ashley, K. Legal Writing: J. Legal Writing Inst. 26 (2022): 329.
• “Prospects for Legal Analytics: Some Approaches to Extracting More Meaning from Legal Texts​​​​​​
• Ashley, K. University of Cincinnati Law Review 90:4 1207-1240 (2022).
• “An Annotation Schema for the Detection of Social Bias in Legal Text Corpora.” Gumusel, E., V. Malic, D. Donaldson, K. Ashley, and X. Liu. In International Conference on Information, 185-194. Springer, Cham, 2022.
• “Toward Summarizing Case Decisions via Extracting Argument Issues, Reasons, and Conclusions” H. Xu, J. Šavelka, and K. Ashley, Eighteenth International Conference on Artificial Intelligence and Law (ICAIL 2021), pp. 250-254.
• “Lex Rosetta: Transfer of Predictive Models Across Languages, Jurisdictions, and Legal Domains” Savelka, J. Westermann, H., Benyekhlef, K., Alexander, C., Grant, J., Amariles, D., El-Hamdani, R., Meeus, S., Troussel, A., Araszkiewicz, M., Ashley, K., Ashley, A., Branting, K., Falduti, M., Grabmair, M., Haravsta, J., Novotna, T., Tippett, E., Johnson, S. Eighteenth International Conference on Artificial Intelligence and Law (ICAIL 2021), pp. 164-173.
• "Discovering Explanatory Sentences in Legal Case Decisions Using Pre-trained Language Models."J. Šavelka and K. Ashley. In Findings of the Association for Computational Linguistics: EMNLP 2021, pp. 4273-4283, 2021.
• "Accounting for Sentence Position and Legal Domain Sentence Embedding in Learning to Classify Case Sentences" Xu, H., J. Savelka, and K. Ashley. In Legal Knowledge and Information Systems, pp. 33-42. IOS Press, 2021.
• “Legal Information Retrieval for Understanding Statutory Terms”. Savelka, J. and Ashley, K. (2021) Artificial Intelligence and Law. https://doi.org/10.1007/s10506-021-09293-5. Pp. 1-45.
• “A Law School Course in Applied Legal Analytics and AI”. Savelka, J., Grabmair, M. and Ashley, K. (2021) Law in Context, 37 (1): 1-41.
• “Using AI to Analyze Patent Claim Indefiniteness”. Alderucci, D., & Ashley, K. (2020). IP Theory, 9(1), 2.
• “Using Argument Mining for Legal Text Summarization.” H. Xu, J. Šavelka, and K. Ashley (2020) Legal Knowledge and Information Systems JURIX (2020): 184-193. IOS Press.
• “Sentence Embeddings and High-Speed Similarity Search for Fast Computer Assisted Annotation of Legal Documents.” H. Westermann, J. Šavelka, V. Walker, K. Ashley, and K. Benyekhlef (2020) Legal Knowledge and Information Systems JURIX (2020): 164-173. IOS Press.
• “Learning to Rank Sentences for Explaining Statutory Terms.” J. Savelka and K. Ashley (2020) Proceedings of the 2020 Workshop on Automated Semantic Analysis of Information in Legal Text (ASAIL) CEUR-WS.org/Vol-2764/paper7.pdf.
• “Improving Sentence Retrieval from Case Law for Statutory Interpretation.” J. Savelka, H. Xu, & K. Ashley (2019) Seventeenth International Conference on Artificial Intelligence and Law, ICAIL 2019. pp. 113-122. Montreal.
• “Using Factors to Predict and Analyze Landlord-Tenant Decisions to Increase Access to Justice.” H. Westermann, V. Walker, K. Ashley, & K. Benyekhlef (2019) Seventeenth International Conference on Artificial Intelligence and Law, ICAIL 2019. pp. 133-142. Montreal.
• "Automatic Summarization of Legal Decisions Using Iterative Masking of Predictive Sentences.” L. Zhong, Z. Zhong, Z. Zhao, S. Wang, K. Ashley, and M. Grabmair. (2019) Seventeenth International Conference on Artificial Intelligence and Law, ICAIL 2019. pp. 163-172. Montreal.
• “Computer-Assisted Creation of Boolean Search Rules for Text Classification in the Legal Domain.” Westermann, H., Savelka, J., Walker, V. R., Ashley, K. D., & Benyekhlef, K. (2019, December). In Legal Knowledge and Information Systems: JURIX 2019: The Thirty-second Annual Conference (Vol. 322, p. 123). IOS Press.
• “Segmenting U.S. Court Decisions into Functional and Issue Specific Parts” J. Savelka and K. Ashley (2018). The 31st International Conference on Legal Knowledge and Information Systems Jurix 2018. Pp. 111-120. Groningen, Neth.
• “Utilizing Vector Space Models for Identifying Legal Factors from Text.” M. Falakmasir and K. Ashley (2017) The 30th International Conference on Legal Knowledge and Information Systems. Jurix 2017. December. Luxembourg.
• “Detecting Agent Mentions in U.S. Court Decisions.” J. Savelka and K. Ashley (2017) The 30th International Conference on Legal Knowledge and Information Systems. Jurix 2017. pp. 39-48. December. Luxembourg.
• “Using Conditional Random Fields to Detect Different Functional Types of Content in Decisions of United States Courts with Example Application to Sentence Boundary Detection.” J. Savelka and K. Ashley, in Proceedings, Second Workshop on Automated Detection, Extraction and Analysis of Semantic Information in Legal Texts (ASAIL) June, 2017, London, UK.
• “Sentence Boundary Detection in Adjudicatory Decisions in the United States.” Savelka, J., Walker, V. R., Grabmair, M., & Ashley, K. D. (2017). Traitement Automatique des Langues, 58(2), 21-45.
• “Experimental Evidence for Diagramming Benefits in Science Writing”. Barstow, B., Fazio, L, Schunn, C., and Ashley, K. (2017), Instructional Science, 45(5), 537-556.
• “The Impacts of Domain-General vs. Domain-Specific Diagramming Tools on Writing”. Barstow, B., Fazio, L., Lippman, J., Falakmasir, M., Schunn, C., and Ashley, K. International Journal of Artificial Intelligence in Education. doi:10.1007/s40593-016-0130-z. pp 1–23 (2016).
• “Network Analysis of Manually-Encoded State Laws and Prospects for Automation” Sweeney PM, Bjerke EF, Potter MA, Guclu H, Keane CR, Ashley KD, Grabmair M, Hwa R (2014) In Winkels, R; Lettieri, N; Faro, S (Eds.) Network Analysis in Law, Collana: Diritto Scienza Tecnologia/Law Science Technology – Temi, 3, pp. 53-78. Napoli: Edizione Scientifiche Italiane.
• “Eliciting Formative Assessment in Peer Review”, Goldin, I. and Ashley, K. D. (2012) Journal of Writing Research. 4(2) pp. 203-237. Special issue on Redesigning Peer Review Interactions Using Computer Tools.
• “Validity and Reliability of an Instrument for Assessing Case Analyses in Bioengineering Ethics Education.” (2015) Goldin, I., Pinkus, R., Ashley, K. Science and Engineering Ethics. 21.3: 789-807.
• Kevin Ashley and I. Goldin, Computer-Supported Peer Review in a Law School Context, U. of Pittsburgh Legal Studies Research Paper Series No. 2012-24, 2012. Available on SSRN.
• Peering Inside Peer Review with Bayesian Models, Artificial Intelligence in Education: The Fifteenth International Conference on Artificial Intelligence in Education (with Goldin, I.) (2011).
• Facilitating Case Comparison Using Value Judgments and Intermediate Legal Concepts, Proceedings of the Conference. Thirteenth International Conference on Artificial Intelligence and Law (with Grabmair, M.) (2011).
• Can Temporal Representation and Reasoning Make a Difference in Automated Legal Reasoning? Lessons from an AI-based Ethical Reasoner, Proceedings of the Conference. Thirteenth International Conference on Artificial Intelligence and Law (with McLaren, B.M.) (2011).
• Toward AI-enhanced Computer-supported Peer Review in Legal Education, in Atkinson K.M., editor. Legal Knowledge and Information Systems, Jurix 2011: The 24th Annual Conference, (2011), Vienna, Austria, Amsterdam: IOS Press, (with Goldin, I.) (2011).
• Toward Extracting Information from Public Health Statutes using Text Classification and Machine Learning, Legal Knowledge and Information Systems, Jurix 2011: The 24th Annual Conference, (2011), Vienna, Austria Amsterdam: IOS Press, (with Grabmair, M.) (2011).
• Kevin Ashley and Will Bridewell, Emerging AI & Law approaches to automating analysis and retrieval of electronically stored information in discovery proceedings, 18 Artificial Intelligence and Law 311 (2010).
• Kevin Ashley, I. Goldin and R. Pinkus, Validity and Reliability of an Instrument for Assessing Case Analyses in Bioengineering Ethics Education, Science and Engineering Ethics (forthcoming).
• Kevin Ashley, N. Pinkwart, C. Lynch and V. Aleven, Formative Evaluations Studies of an Intelligent Tutoring System for Making Legal Arguments with Hypotheticals. 19 International Journal of Artificial Intelligence in Education. (2009).
• Teaching a Process Model of Legal Argument with Hypotheticals, 17 Journal of Artificial Intelligence and Law 321 (2009).
• K. D. Ashley and S. Brüninghaus, Automatically Classifying Case Texts and Predicting Outcomes, 17 Artificial Intelligence and Law 125 (2009).
• Kevin Ashley, N. Pinkwart, V. Aleven and C. Lynch, Adaptive Rückmeldungen im intelligenten Tutorensystem LARGO, 5 elearning and education (online journal) (2009).
• Kevin D. Ashley, Comment on Lowrance's Graphical Manipulation of Evidence in Structured Arguments Law, 6 Probability & Risk 241, (2007).
• Kevin D. Ashley & S. Brüninghaus, Computer Models for Legal Prediction, 46 Jurimetrics J. 309 (2006).
• Kevin D. Ashley, Capturing the Dialectic Between Principles and Cases, 44 Jurimetrics J. 229 (2004).
• Kevin D. Ashley et al., Law, Learning and Representation, 150 Artificial Intelligence 17 (2003).
• Kevin D. Ashley et al., Case-Based Reasoning and Law, 20 Knowledge Engineering Review, 293 (2005).
• Kevin D. Ashley, Hypothesis Formation and Testing in Legal Argument in International Congress of Comparative Cultures and Legal Systems Of The Instituto De Investigaciones Juridicas Second International Meeting On Artificial Intelligence And Law, Universidad Nacional Autonoma de Mexico, Mexico City (April 2006).
• Kevin D. Ashley, V. Aleven & C. Lynch, Teaching Creative Legal Reasoning with Examples from Supreme Court Oral Arguments in Proceedings of the ICAIL-05 Workshop on Artificial Intelligence and Legal Education 47, Bologna (2005).
• V. Aleven & Kevin D. Ashley, Toward Supporting Hypothesis Formation and Testing in an Interpretive Domain in Proceedings Of The Twelfth International Conference On Artificial Intelligence In Education, Amsterdam (July 2005).
• Kevin D. Ashley, Case-Based Models of Legal Reasoning in a Civil Law Context for International Congress of Comparative Cultures and Legal Systems of The Instituto De Investigaciones Juridicas, Universidad Nacional Autonoma de Mexico, Mexico City, (February 2004).
• Kevin D. Ashley, Exploring an Example of Creative Legal Problem Solving: Inventing the NOW Account for the Special Workshop of the IVR World Congress 2003 on Creativity In Legal Problem Solving, Lund Sweden (August 2003).

Presentations

• Presented invited talk, “Using Generative AI to Model Case-based Legal Argument,” at the 27^th Aula Magna, Pontifical Catholic University of Peru, Lima. November 27, 2023.
• Presented invited talk, “Modeling Case-based Legal Argument in an Age of Generative AI,” IDEAL workshop on CS, Law, and Policy Oct. 25, 2023. Northwestern University.
• Presented invited talk, “Recent Developments in Legal Text Analytics”, U. Miami School of Law, March 9, 2023 ​​​​​​.
• Presented invited series of lectures at the University of Bologna, CIRSFID, entitled, “Introduction to AI and Law,” “Models of Legal Argument: A Case-based Approach to Reasoning with Values,” “Prospects for Legal Analytics, and “Do Case-Based Models of Legal Reasoning Fit in a Civil Law Context?” December 11-15, 2023.
• Presented invited lectures, “AI & Law, CBR, and Legal Text Analytics,” “Models of legal argument: Case-based Approaches,” and “Prospects for Legal Analytics” at the Summer School on AI & Law, European University Institute, Badia Fiesolana, Italy. July10-14, 2023.
• Presented invited series of lectures at the University of Bologna, CIRSFID, entitled, “Introduction to AI and Law,” “Models of Legal Argument: A Case-based Approach to Reasoning with Values,” and “Prospects for Legal Analytics: Some Approaches to Extract More Meaning from Legal Texts,” December 5-7, 2022.
• Presented invited lectures, “Introduction to AI and Law,” “Case-based Models of Legal Argument,” and “Prospects for Legal Analytics,” virtually at the Summer School on AI & Law, European University Institute, Badia Fiesolana, Italy. July 7 -14, 2022.​​​​​​​
• Presented invited lectures, “Introduction to AI and Law,” “Case-based Models of Legal Argument,” and “Prospects for Legal Analytics,” virtually at the Summer School on AI & Law, European University Institute, Badia Fiesolana, Italy. July 7 -14, 2022.
• Presented invited keynote address, “AI and Law: from Knowledge-based to Machine Learning (and Back?)” virtually at the Computational Legal Studies: Past, Present, and Future Conference, The Centre for Computational Law, Singapore Management University. March 2, 2022.
• Participated in Panel Discussion on key technological characteristics of AI technologies and their role in legal practice re resolving disputes. Autonomy through CyberJustice Technologies Project, University of Montreal. October 6, 2022.
• Invited talk on “Update on Case Summarization Research in NSF Fairness in AI Project, `Using AI to Increase Fairness by Improving Access to Justice’”. Autonomy through CyberJustice Technologies Project, University of Montreal. June 12, 2022.
• Invited remote talk on “How Can Text Analytics Explain Legal Predictions?” at Conference on Artificial Intelligence and Judicial Big Data, Huazhang University of Science and Technology, October 15, 2022.
• Presented invited talk, “Legal Text Analytics and its Role in AI and Law”, Princeton Chapter of ACM, May 19, 2022​​​​​​​.
• Presented invited talk, “Research Progress in Legal Text Analytics,” virtually at the Symposium on Artificial Intelligence and Law co-organized by IIT Kharagpur, IIT Kanpur, IISER Kolkata, TCG CREST, WBNUJS, and Vidhi Centre for Legal Policy (all from India) and CSIRO Australia.  June 2, 2021.
• Presented invited short talk, “Applying Text Analytic Methods to Drug Interdiction Auto Stop Cases” virtually at the CrossJustice Final Conference on Empowering Defence Rights through Algorithms and AI. University of Bologna. February 25, 2022.​​​​​​​
• Presented invited talk, “Teaching Applied Legal Analytics and A.I. in Law School” Case Western Reserve University, School of Law, July 14, 2022. 2
• Co-presented invited talks, “Alexa! Write a Memo”: The Promise and Challenges of AI and Legal Writing, at the Symposium on Artificial Intelligence and the Legal Profession, Legal Writing Institute, September 25, 2021 and at the Legal Writing Institute Symposium, Western Regional Legal Writing Conference, November 13, 2022. ​​​​​​​
• Organized and moderated program on Legal Text Analytics and Empirical Legal Studies virtually in the CS+Law Research Presentations and Discussions Series featuring “Large Language Models and the Law,” Prof. Daniel E. Ho, Stanford University, and “Reading (Judges') Minds with Natural Language Processing,” Prof. Elliott Ash, ETH Zurich. March 11, 2022.
• Presented invited talk, “Hot Topics in Legal Text Analytics,” virtually in The Technological Innovation and Law (TIL) 2021
• Program on Human brain - AI - Law. University of Pavia.  September 16, 2021. ​​​​​​​
• Participated in panel discussion on “Developments in LegalTech” and delivered short presentation entitled “New Developments in Legal Text Analytics” at University of Cincinnati College of Law Corporate Law Symposium, Advances in Legal Analytics, March 12, 2021.
• ​​​​​​​Presented invited talk entitled “Progress in Teasing Meaning from Legal Texts”  in AI@TR Invited Speaker Series, Thomson Reuters, March 2, 2021.
• Participated in panel discussion on “Data as Power” and delivered short presentation entitled “Legal Text Data as Power! (some limitations may apply)” at the Law Review Symposium: Artificial Intelligence and the Law, West Virginia University College of Law,  February 26, 2021.​​​​​​​
• Participated in panel discussion on Computation and Legal Services and delivered short presentation entitled “Opportunities and Challenges of Legal Text Analytics” at Northwestern University Academic Symposium, Law + Computation: An Algorithm for the Rule of Law and Justice? February 5, 2021.
• Presented invited talk entitled “The Role of AI in Legal Analytics” virtually at the Centre of Excellence in Cyber Law and Data Protection Law, ICFAI Law School, IFHE, Hyderabad, India. January 29, 2021.​​​​​​​
• Presented invited lectures, “Introduction to AI and Law,” “Case-based Models of Legal Argument,” and “Prospects for Legal Analytics,” virtually at the Summer School on AI & Law, European University Institute, Badia Fiesolana, Italy. July 8-16, 2021.​​​​​​​
• Presented invited lectures, “Legal Text Analytics: Opportunities and Challenges,” virtually in Prof. Monica Palmirani’s Seminar on Data Science for Legal Analytic at the University of Bologna. May 10, 2021, and “Hot Topics in Legal Text Analytics,” virtually in Prof. Monica Palmirani’s Course on Data Science for Lawyers at the University of Bologna. November 22, 2021.
• Presented invited lecture, “Computational Models of Case-Based Reasoning,” and participated in a Panel discussion: Law, AI, and Ethics, virtually at the 1st Munich Legal Tech Summer School, Technical University of Munich, Germany. August 3, 2021.​​​​​​​
• Presented invited keynote address entitled “Progress in Teasing Meaning from Legal Texts” at the International Workshop on Mining and Learning in the Legal Domain (MLLD-2020) of the 20th IEEE International Conference on Data Mining (virtual), November 17, 2021.
• Presented short talk entitled “A Law School Course to Teach  Applied Legal Analytics and AI” at SubTech 2020 (virtual), July 16, 2020.
• ​​​​​​​Presented invited keynote address entitled “Teaching Law Students about AI and Text Analysis” at the Research Meets Practice (ReMeP) Legal Informatics Conference (virtual), June 8, 2020.
• Co-presented invited talk entitled “Artificial Intelligence for Corporations and Law Firms:​​​​​​​​​​​​​​
• I presented an invited talk entitled “Automatically Extracting Meaning from Legal Texts: Opportunities and Challenges” at the University of Pittsburgh School of Law in March 2020.​​​​​​​
• New Tools and Unmet Possibilities,” with Practicing Law Institute, San Francisco (via Zoom), April 2020.​​​​​​​
• Presented invited keynote lecture entitled “Teaching Legal Analytics and AI to Law Students” at the European Center for Law, Science, and New Technologies, University of Pavia, February, 2020.
• Participated in panel discussion at “AI and Justice in 2035” Roundtable and presented paper entitled “(When) Will Legal Apps Be Able to Read like Lawyers?” University of California at Los Angeles School of Law, Los Angeles, CA. February, 2020.​​​​​​​
• Presented invited talk entitled “Teaching Legal Analytics and AI to Law Students” at the 4th International Workshop on MIning and REasoning with Legal texts (MIREL), Madrid. December, 2019.
• Presented talk entitled, "How to Teach Applied Legal Analytics and AI to Law Students, a Report" at Stanford Law School as part of  the CodeX Speaker Series, sponsored by the Stanford CodeX: Center for Legal Informatics.  November, 2019.​​​​​​​
• Presented invited seminars at the Summer School on AI and Law 2019, European University Institute, Department of Law entitled, “Introduction to and Short History of Artificial Intelligence & Law,” “Models of Case-Based Legal Argument,” and “Case Outcome Prediction from Text.”
• Presented invited talk entitled “Automatically Extracting Meaning from Legal Texts: Opportunities and Challenges,” at the International Conference on New Technologies and Law, Hangzhou Normal University Law School, Hangzhou, China, and invited talks entitled, “Modeling Case-Based Legal Reasoning,” and “Automatically Extracting Meaning from Legal Texts: Opportunities and Challenges,” at the Faculties of Law, Zhejiang University, Hangzhou, and Nanjing University, Nanjing, China, June / July, 2019.
• Presented two invited public lectures entitled “Text Analytics in Legal Practice: Opportunities and Challenges” at the University of Queensland, Technology and the Future of the Legal Profession Program, and at the Supreme Court of Queensland, Brisbane, Australia. May 16, 2019.
• Invited talk entitled “Connecting Case Texts and Computational Models of Legal Reasoning” at Plenary Session of Conference on Artificial Intelligence: Thinking About Law, Law Practice, and Legal Education, Duquesne University School of Law. Pittsburgh, Pennsylvania. April 26, 2019.
• Invited talk entitled “Automatically Extracting Meaning from Legal Texts: Opportunities and Challenges.” Georgia State University Law Review Symposium - Legal Intelligence through Artificial Intelligence. April 5, 2019.
• Invited keynote lecture entitled “Artificial Intelligence and Legal Analytics: New Tools for Law Practice in the Digital Age” at the Legal Datamining Conference, HEC Paris, France. March 21, 2019.
• Invited talk entitled “Annotating Cases and Statutes for Legal Pedagogy (and Machine Learning)” at Legal Writing Institute One-Day Workshop, Leveraging Technology in the Legal Writing Classroom to Prepare Law Students for Practice, University of Pittsburgh School of Law, November 30, 2018.
• Recorded podcast interview for London School of Economics Alumni Association London series entitled “Law 2.0 Legal Services & Emerging Tech". October 17, 2018.
• Invited talk entitled “Annotating Texts for Legal Pedagogy and  Machine Learning” at Board of Visitors Meeting, Learning Research and Development Center, University of Pittsburgh. October 13, 2019.
• Invited talk entitled “Legal Text Analytics: Opportunities and Challenges Where Law and AI Meet” at University of São Paulo Colloquium, Brazil. September 22, 2018.
• Invited talk entitled “Legal Text Analytics: Opportunities and Challenges Where Law and AI Meet” at the Second International Congress of Law, Government & Technology, University of Brasília. Brazil. September 21, 2018.
• Invited talk entitled “Addressing a Challenge for US Legal Education: A Law School Course on Applied Legal Data Analytics & AI” at the Fifteenth International Conference on Substantive Technology in Legal Education and Practice (SubTech 2018), IT Law Programme at the University of Tartu. Tallinn, Estonia. July 13, 2018.
• Invited talk entitled “Accounting for Legal Values.” Computational Legal Studies Workshop. University of Hong Kong. June, 2018.
• Invited talk entitled “Legal Text Analytics or How Law Meets AI; Opportunities and Challenges.” Luxembourg Institute of Science and Technology. 23 May 2018.
• Invited keynote address entitled “Applying Text Analytics in the Legal Domain: Possibilities and Problems.” Legal Aspects of Data Science Conference. Tilburg University, The Netherlands. 18 May 2018.
• Presented invited talk entitled “Artificial Intelligence and Legal Practice” at the University of Heidelberg (U. Heidelberg) Faculty of Law Doctoral Research Group in "Digital Law" (i.e., Promotionskolleg Digitales Recht). Germany. 16 May 2018.
• Presented invited talk entitled “Introducing Legal Hypotheses and Hypothetical Reasoning” at the Karlsruhe Institute of Technology, Institute of Philosophy. Karlsruhe, Germany. 15 May 2018.
• Presented invited talk entitled “Computationally Modeling Case-Based Legal Reasoning” at the Karlsruhe Institute of Technology, Institute of Theoretical Informatics. Karlsruhe, Germany. 14 May 2018.
• Presented invited talk entitled “Semantic Analysis of Legal Texts: Challenges and Opportunities” at the Technical University of Munich, Department of Informatics, Program on Software Engineering for Business Information Systems. Germany. 7 May 2018.
• Presented invited research seminar entitled “Argumentation with Value Judgments; An Example of Hypothetical Reasoning” at the Institute of Philosophy, Karlsruhe Institute of Technology. Karlsruhe, Germany. 5 May 2018.
• Presented invited talk entitled “Modeling Case-Based Legal Reasoning” at the University of Ulm. Germany. May 3, 2018.
• Invited talk entitled “Legal Liability of Autonomous Systems and Implications for Norms-based Systems: an Overview.” Dagstuhl Seminar 18171, Normative Multi-Agent Systems. 23 April 2018.
• Invited presentation entitled "Artificial Intelligence and Legal Practice". In Wells Fargo Law Firm Client Luncheon. Chicago, IL. March 19, 2018.
• Invited presentation entitled "Artificial Intelligence and Legal Practice". In Wells Fargo Law Firm Client Luncheon. Houston, TX. February 21, 2018.
• Invited presentation entitled "Artificial Intelligence and Legal Practice". In Wells Fargo Law Firm Client Luncheon. Dallas, TX. February 20, 2018.
• Invited presentation entitled "Artificial Intelligence and Legal Practice". In Wells Fargo Law Firm Client Luncheon. Miami, FL., February 10, 2018.
• Helped organize and participated in presenting program entitled "Artificial Intelligence and Legal Practice" for the Allegheny County Bar Association. Pittsburgh, PA. February 2, 2018.
• Invited presentation entitled "Utilizing Vector Space Models for Identifying Legal Factors from Text". At the 30th International Conference on Legal Knowledge and Information Systems. Jurix 2017. Luxembourg. December 14, 2017.
• Panel presentation for Jurix 2017 Workshop on Legal Data Analysis panel on “The Future of Legal Data Analysis?” The 30th International Conference on Legal Knowledge and Information Systems. Jurix 2017. Luxembourg. December 2017.
• Invited talk entitled "Utilizing Vector Space Models for Identifying Legal Factors from Text". In National Institute of Informatics. Tokyo, Japan. November 15, 2017.
• Invited keynote speech entitled "Mining Information from Statutory Texts: A Case Study". In Eleventh International Workshop on Juris-informatics (JURISIN 2017). Tokyo, Japan. November 14, 2017.
• Invited tutorial entitled "An Introduction to Artificial Intelligence and Law." In National Institute of Informatics. Tokyo, Japan. November 13, 2017.
• Presented invited graduate seminars on Artificial Intelligence and Legal Analytics. In Digital Law program of the University of Heidelberg Faculty of Law. Heidelberg, Germany. (2018, January 15).
• Invited panel participation entitled "Artificial Intelligence (AI) in the Legal Industry: The role of AI and its impacts". In Wells Fargo Law, Leadership and Vision 2017 Meeting. Washington, DC. (2017, June 6).
• Invited presentation for Jurix 2016 Workshop on Legal Data Analysis in a panel discussion entitled, “How should law be communicated and analyzed on the example of international law?” entitled, “Some examples involving public health law of multiple states”. December 14, Inria Sophia Antipolis Mediterranée, Antibes, France.
• Invited presentation entitled, “Harnessing Argument Mining for Conceptual Legal Information Retrieval” for the Annual Conference of the Cyberjustice Laboratory, Université de Montréal, entitled “On Recent Developments in Artificial Intelligence: Law and Justice,” in a panel called “New Developments in Cyberjustice and Law: Computational Law,” October 27, 2016.
• Delivered invited talk entitled, “Putting Argument Mining to Work: An Experiment in Legal Argument Retrieval using the LUIMA Type System And Pipeline”, at the SubTech 2016 Conference at the University of Richmond School of Law, July, 2016.
• Delivered invited presentation entitled, “Legal Argument Retrieval Using LUIMA” at the Vanderbilt University Law School AI & Law Workshop Program on Law & Innovation. April, 2016. Nashville, TN.
• Delivered presentation entitled “Putting Argument Mining to Work: an Experiment in Legal Argument Retrieval Using the LUIMA Type System and Pipeline”. K. Ashley (2016) Dagstuhl Seminar 16161– Natural Language Argumentation: Mining, Processing, and Reasoning over Textual Arguments. April.
• Delivered paper entitled “A Global Perspective on Argument Diagramming to Support Writing Skills”, K. Ashley, M. Falakmasir (2015) 7th International Conference on Education and New Learning Technologies, EDULEARN15 Proceedings, pp. 7354-7363. Barcelona, July.
• Delivered paper entitled “Applying an Interactive Machine Learning Approach to Statutory Analysis” Savelka, J., Trivedi, G., & Ashley, K. in A. Rotolo (Ed.) Proceedings, 28th Annual Conference on Legal Knowledge and Information Systems (Jurix 2015). Best Student Paper Award. Universidade do Minho, Portugal.
• Delivered position paper entitled, “Applying Argument Extraction to Improve Legal Information Retrieval” at the Frontiers and Connections between Argumentation Theory and Natural Language Processing Conference, Centro Residenziale Universitario di Bertinoro, Italy, July 2014.
• Delivered invited talk entitled, “Toward Integrating Computational Models and Legal Texts (or will IBM Debater beat us to it?)”, at the Thirteenth International Conference on Substantive Technology in the Law School and Law Practice (Subtech 2014), University of Vienna Law School, July 11, 2014.
• Co-delivered invited talk entitled, “Computer-Supported Peer Review in a Law School Context” at the Conference for Law School Computing (CALIcon 2014), Harvard Law School, June, 2014.
• Delivered invited talk entitled, “A Global Perspective on Argument Diagramming to Support Writing Skills”. Presented at: Board of Visitors Meeting; 2014 Apr 25; Learning Research and Development Center.
• Co-delivered invited talk entitled, “Modeling Purposive Legal Argumentation as a Comparison of Value Effects Entailed by Situations,” at the University of San Diego Center for Computation, Mathematics, and the Law (CCML) Inaugural Workshop. March 2014.
• Delivered invited talks entitled, "Toward Integrating Computational Models and Legal Texts," at Stanford Law School as part of the CodeX Speaker Series, sponsored by the Stanford CodeX: Center for Legal Informatics. February 2014.
• Delivered paper entitled, “From Information Retrieval (IR) to Argument Retrieval (AR) for Legal Cases: Report on a Baseline Study,” at the 26th Annual Conference on Legal Knowledge and Information Systems (Jurix 2013) Bologna. December, 2013.
• Delivered paper entitled, “Network Analysis of Manually-Encoded State Laws and Prospects for Automation,” at Workshop on Network Analysis in Law at the XIV International Conference on AI and Law (ICAIL 2013) Rome, June 14, 2013.
• Delivered research abstract entitled, “Toward Constructing Evidence-Based Legal Arguments Using Legal Decision Documents and Machine Learning,” at the Fourteenth International Conference on Artificial Intelligence and Law. ICAIL 2013. June. Rome, Italy.
• Co-delivered invited talk entitled, “Text Classification and Machine Learning” at the MIDAS Workshop on Engaging Computational Methods for Public Health Law, October, 2013, Pittsburgh.
• Presenter, “Applying Artificial Intelligence to Law: Lessons Learned and Future Directions,” at Masaryk Univ. Faculty of Law, Czech Republic, October 2011.
• Presenter, “Research Progress in Artificial Intelligence and Law: An Intellectual Survey,” Faculty of Law, Univ. of Bologna, Bologna, Italy, October- November 2011.
• Presenter, “Toward AI-enhanced Computer-supported Peer Review in Legal Education,” Jurix 2011: The 24th Annual Conference, Vienna, Austria December 2011.
• Presenter, “Toward Teaching Writing and Argumentation with AI-Supported Peer Review,” Center for e-Learning Technology, Saarland Univ. and German Research Center for Artificial Intelligence, Saarbrücken, Germany, May 2012.