15 reports and papers on law and technology, divided between corporate, academic, professional bodies and nonprofit categories:
| author | title | category | year |
|---|---|---|---|
| Alari et al | How Artificial Intelligence Will Affect the Practice of Law | Academic | 2018 |
| The Law Society | Algorithms in the Criminal Justice System | Professional Body | 2019 |
| Vinson & Moppett | Digital Pro Bono: Leveraging Technology to Provide Access to Justice | Academic | 2019 |
| Deloitte Ltd | Objections overruled : The case for disruptive technology in the legal profession | Corporate | 2017 |
| The Law Society | Horizon Scanning: Artificial Intelligence and the Legal Profession | Professional Body | 2018 |
| Jackson | Human-centered legal tech: integrating design in legal education | Academic | 2016 |
| Legal Services Board | Technology and Innovation in Legal Services | Professional Body | 2018 |
| Kerikmäe et al | Legal Technology for Law Firms: Determining Roadmaps for Innovation | Academic | 2018 |
| The Law Society | Lawtech Adoption Research | Professional Body | 2019 |
| Caserta & Madsen | The Legal Profession in the Era of Digital Capitalism: Disruption or New Dawn? | Academic | 2019 |
| Bench-Capon et al | A history of AI and Law in 50 papers: 25 years of the international conference on AI and Law | Academic | 2012 |
| Schoonmaker | Withstanding Disruptive Innovation: How Attorneys Will Adapt and Survive Impending Challenges from Automation and Nontraditional Legal Services Providers | Academic | 2019 |
| The Engine Room | Technology for Legal Empowerment: A Global Review | Nonprofit | 2019 |
| Solicitors Regulation Authority | Technology and legal services | Professional Body | 2018 |
| Yu & Ali | What’s Inside the Black Box? AI Challenges for Lawyers and Researchers | Academic | Yu & Ali |
A 16 topic model using the R STM Package (https://www.structuraltopicmodel.com/) was created, giving the following topics (manually named):
Fig1: Topics and Correlations
Of the themes discovered the largest contrast between categories was the emphasis on users and access between nonprofit and other authors:
Fig 2: Users and Access Emphasis
Another divergence was the data-centric view of ‘online services’ from the corporate report in contrast to the more organisational-centric view from other sources:
Fig 3: Data-Centric Online Services Emphasis
Comparing the ‘Users and Access’ topic with the System Development one illustrates the different emphasis from user-centric to firm-centric
Fig 4: User topic compared to systems development
We also see by comparing historic AI research with modern approaches the evolution from rules-based, logic-based systems to connectionism and learning-from-example:
Fig 5: Machine Learning compared to Reason and Argument
..perhaps the time is ripe for re-integrating these two poles?