Slides presented at the British and Irish Law Education and Technology Association (BILETA) 2018 conference. The topic is how to integrate teaching of Law and Computer Science to forward Law and Technology research, development, and exploitation.
AI in legal practice – the research perspectiveAnna Ronkainen
1) The document discusses AI in legal practice from a research perspective.
2) It defines AI as using computers to do things that people can do easily but computers cannot, such as legal tasks like document review, due diligence, and trademark search and clearance.
3) The author notes that AI and law is an established research field since the 1980s, and legal applications of AI research like natural language processing are now a wake-up call for the field.
Finnish Legal Tech Forum launch presentationAnna Ronkainen
Legal technology refers to technology used by lawyers or to perform legal work conventionally done by lawyers. The Finnish Legal Tech Forum is a new organization promoting legal tech in Finland with around 40 members. It plans to take over the Helsinki Legal Tech Meetup and hold events to discuss topics like online dispute resolution and legal tech startups. The presentation provided an overview of legal tech areas and upcoming conferences and meetups for people to learn more.
On May 19, 2016 I hosted a workshop at Stanford's Codex Center about ways to make legal data more open and accessible for computation. These are the slides from my presentation framing the issue.
General introduction to legal technology and legal AI, presented at the inaugural Helsinki Legal Tech Meetup on 2016-03-17 (for a more thorough overview, please see my Introduction to Legal Technology slides for lectures 1–10, also on SlideShare)
1) Artificial intelligence will have two major impacts on law - how legislation is shaped and how legal professions operate.
2) Legal analytics applies big data analytics methods to analyze large amounts of legal data to assist with tasks like legal research, predicting litigation outcomes, and creating legal documents.
3) The legal analytics market is growing rapidly and is led by large companies but also presents opportunities for startups, though most services currently operate in the US.
This document discusses different perspectives on cyberethics:
1) Professional ethics examines ethical responsibilities of computer professionals.
2) Philosophical ethics analyzes the nature and social impact of technology through ethical theories.
3) Descriptive ethics reports on the actual effects of technology without judgment, informing later normative analysis.
Cyberethics incorporates all three perspectives to understand technology's descriptive effects and prescribe ethical policies and conduct.
This document provides an overview of the topics that will be covered in a course on professional practices in information technology (IT). The course will cover introductions to IT and professionalism, ethics, information security and privacy, intellectual property laws, and social responsibilities of IT professionals. It will also discuss how IT is used in different domains like education, health, finance, entertainment, and careers. The document outlines different computer types including supercomputers, mainframes, workstations, microcomputers, and microcontrollers. It also discusses topics like servers, trends of convergence, portability and personalization in IT, and future directions of computer and communication technologies.
AI in legal practice – the research perspectiveAnna Ronkainen
1) The document discusses AI in legal practice from a research perspective.
2) It defines AI as using computers to do things that people can do easily but computers cannot, such as legal tasks like document review, due diligence, and trademark search and clearance.
3) The author notes that AI and law is an established research field since the 1980s, and legal applications of AI research like natural language processing are now a wake-up call for the field.
Finnish Legal Tech Forum launch presentationAnna Ronkainen
Legal technology refers to technology used by lawyers or to perform legal work conventionally done by lawyers. The Finnish Legal Tech Forum is a new organization promoting legal tech in Finland with around 40 members. It plans to take over the Helsinki Legal Tech Meetup and hold events to discuss topics like online dispute resolution and legal tech startups. The presentation provided an overview of legal tech areas and upcoming conferences and meetups for people to learn more.
On May 19, 2016 I hosted a workshop at Stanford's Codex Center about ways to make legal data more open and accessible for computation. These are the slides from my presentation framing the issue.
General introduction to legal technology and legal AI, presented at the inaugural Helsinki Legal Tech Meetup on 2016-03-17 (for a more thorough overview, please see my Introduction to Legal Technology slides for lectures 1–10, also on SlideShare)
1) Artificial intelligence will have two major impacts on law - how legislation is shaped and how legal professions operate.
2) Legal analytics applies big data analytics methods to analyze large amounts of legal data to assist with tasks like legal research, predicting litigation outcomes, and creating legal documents.
3) The legal analytics market is growing rapidly and is led by large companies but also presents opportunities for startups, though most services currently operate in the US.
This document discusses different perspectives on cyberethics:
1) Professional ethics examines ethical responsibilities of computer professionals.
2) Philosophical ethics analyzes the nature and social impact of technology through ethical theories.
3) Descriptive ethics reports on the actual effects of technology without judgment, informing later normative analysis.
Cyberethics incorporates all three perspectives to understand technology's descriptive effects and prescribe ethical policies and conduct.
This document provides an overview of the topics that will be covered in a course on professional practices in information technology (IT). The course will cover introductions to IT and professionalism, ethics, information security and privacy, intellectual property laws, and social responsibilities of IT professionals. It will also discuss how IT is used in different domains like education, health, finance, entertainment, and careers. The document outlines different computer types including supercomputers, mainframes, workstations, microcomputers, and microcontrollers. It also discusses topics like servers, trends of convergence, portability and personalization in IT, and future directions of computer and communication technologies.
Cyberethics is the study of moral, legal, and social issues involving cybertechnology and its impact. Cybertechnology refers to computing and communications devices like computers, networks, and the Internet. The history of cyberethics includes four phases defined by the evolving technologies from standalone machines to today's converged technologies. While some argue cyberethics issues are not unique, others believe new issues have emerged due to the scale and scope enabled by cybertechnology, like the ability to stalk multiple victims globally without leaving home.
This chapter discusses computer and internet crime. It begins by outlining the objectives of understanding key ethical issues around data security, reasons for the rise in security incidents, common attack types, perpetrator objectives, and elements of a multilayer security process. It then discusses why incidents are so prevalent due to increasing complexity, user expectations, and reliance on commercial software with vulnerabilities. Common attack types like viruses, worms, Trojan horses, and phishing are also outlined. The chapter concludes by discussing prevention, detection, response, and establishing security policies and risk assessments to implement trustworthy computing.
Machine learning and the challenges of digital transformation in the lawSebastian Ko
The adoption of machine-learning (a form of artificial intelligence) by lawyers is shaping the future of law –as a profession and institution. Today, pockets of practice and traditional workflows have undergone massive transformation, viz. legal research and document reviews in discovery, regulatory disclosures, M&A, and contract management. Many alternative legal services providers, “legaltech” vendors, and other “NewLaw” businesses were born in the 2010s. Yet, truly full-service “robo-lawyers” are nowhere in sight. This seminar will examine –from a legaltech industry perspective– the technological influences on emerging industry trends, including the applications of analytics and natural language processing. The discussion will focus on how software encodes the law and legal processes in software, the related technological and ethical challenges, and the adoption barriers in legal practice.
This document discusses ethical issues related to information systems. It introduces the concept of NORA technology which can find obscure relationships in data from multiple sources, potentially violating privacy. It then outlines principles of ethics like responsibility, accountability, and liability. The document presents a 5-step process for ethical analysis and 6 candidate ethical principles. Professional codes of conduct and real-world dilemmas are discussed. The rest of the document focuses on privacy, outlining US privacy protections and fair information practices that are the basis for many privacy laws. The European data protection directive and US safe harbor framework in response are also summarized.
This document discusses various topics related to intellectual property, including copyrights, patents, trade secrets, plagiarism, reverse engineering, open source software, and cybersquatting. It provides an overview of these key concepts, including definitions, legal protections, limitations, and issues that arise. The objectives are to explain what intellectual property encompasses and why companies work to protect it, as well as discuss strategies, laws, and challenges regarding intellectual property rights in information technology.
The Innovation Gap: Why the Justice System Has Failed to Keep Pace with Techn...Robert Ambrogi
This was my keynote delivered to the Legal Services Corporation's 2018 Innovations in Tech Conference. Few would dispute that technology is one of the keys to addressing the justice gap. Yet at a time when technological innovation abounds, the justice gap grows only wider. The problem is not technology – it is the justice system’s failure to employ it. In this program, we’ll explore the impediments to broader use of technology and what can be done to overcome them.
October 29, 2019, I was invited to present the keynote of the LegalTech Alliance meeting on eDiscovery and Big Data, in which 11 law departments from the Universities of Applied Sciences in the Netherlands participate.
eDiscovery is more and more important than ever. Future legal professionals must be able to deal with large electronic data sets so they can:
- Take decisions based on facts and not based on guesses and assumptions;
- Answer information requests timely, accurately and complete;
- Avoid high cost, reputation damage, regulatory measures, business disruption and stress!
It is great that the LegalTech Alliance understands that need and that they embed eDiscovery in their educational programs.
Attached are slides of the workshop were we presented the course eDiscovery (including the hands-on with ZyLAB) which we developed together with the University of Applied Sciences in Amsterdam
This document defines open data and provides examples of its use. Open data is publicly available data that can be freely used, shared and built upon. Examples like Citymapper, Zillow and FlightAware demonstrate how open data from transportation, real estate and aviation has been used to build useful applications. The document discusses open data essentials, guidelines, formats, sources, challenges and how people can participate by contributing, advocating or finding innovative uses for open data.
Ai and applications in the legal domain studium generale maastricht 20191101jcscholtes
November 20, 2019, it was my great pleasure to present a special lecture on Artificial Intelligence and Application in the Legal Domain. In this lecture I discuss how the development of machines that can learn, reason and act intelligently – Artificial Intelligence (AI) – is advancing rapidly in the legal domain. In some areas, machine intelligence have even already surpassed the limits of what the brightest human minds are capable of achieving, especially in the field of eDiscovery and Legal Review of large data set.
In others, machines still struggle with seemingly basic tasks. Nonetheless, breakthroughs in AI already have profound impact on the legal profession. AI is set to improve our world now and will continue to do so in the future. At the same time, there is the fear of losing control.
This lecture was part of a larger series on AI organized by our department of data science and knowledge engineering: https://www.maastrichtuniversity.nl/events/artificial-intelligence.
More information can be found here: https://textmining.nu
Summary:
The Internet of Things has been touted as the centerpiece of many innovative devices as it grows to encompass nearly every type of product imaginable. Already, appliances, cars and even buildings are being equipped with the capability to access Wi-Fi and wired networks. This has led to new efficiencies and data-driven opportunities for enterprises across the board.
When you hear “the next big thing,” do you think they’re thinking big enough? Attend this webinar to find out more.
Presenter:
This webinar will be presented by Arthur Donkens, the managing partner of ITSX. Arthur has been active in information security since 1986, by advising, auditing and collaborating with more than 30 top class companies. Through his rich experience, he has been issued with credible certificates in information security, and has contributed in this sector by writing articles and whitepapers that are available. His moto is “Balancing security and business goals through well designed security architectures.”
Video here - https://www.youtube.com/watch?v=6fm_rzIL8gA
The Technology Committee of the Clinical Section continues its Webinar series on Tuesday with a webinar about CALS's A2J Author technology.
So you say you want to teach your students using experiential learning, expose them to technology worthy of modern law practice AND increase their awareness of the access to justice gap? With the Center for Computer-Assisted Legal Instruction’s (CALI) A2J Author, you can do this. A2J Author is a web-based tool that lets lawyers automate legal processes or court forms without having to learn to program. It has been used by legal aid and courts to automate over 1000 forms and processes and has been used by SRLs (self-representing litigants) over 3 1/2 million times ... and .... it's free for US law schools to use in their courses.
During the AALS Clinical Section Technology Committee’s upcoming Technology Tuesdays Webinar on March 14, from 4-5 p.m. EST, John Mayer, CALI's Executive Director will demo A2J Author and talk about how it has been used in legal education courses covering a variety of legal subject areas. A2J Author is also an ideal platform for rapid deployment of automation to assist in immigration and hackathon events. Come learn about CALI's best kept secret.
The document discusses technology and summarizes key points from a presentation on the topic. It begins by defining the term "geek" and discussing the need to understand one's audience. It then explains that a "black box" refers to something that can be understood based on its inputs, outputs, and functions without knowing its internal workings. The document summarizes views of business, applications, and technology from both top-down and bottom-up perspectives. It also discusses requirements, service management, cloud computing models, and provides a high-level look at potential future directions for IT.
Data is everywhere and in everything we do. Most of the time, usable information is hidden in raw data and because of that, there is an increasing demand for people capable of working creatively with it. To fully understand how we can assist data science workers to become more productive in their jobs, we first need to understand who they are, how they work, what are the skills they hold and lack, and which tools they need. In this paper, we present the results of the analysis of several interviews conducted with data scientists. Our research allowed us to conclude that the heterogeneity between these professionals is still understudied, which makes the development of methodologies and tools more challenging and error prone. The results of this research are particularly useful for both the scientific community and industry to propose adequate solutions for these professionals.
Digital forensics involves extracting evidence from digital devices like computers. This usually involves extracting and interpreting the contents and meaning of files. There has been growing interest in digital forensics courses across many academic disciplines. Some challenges include artificial limitations imposed by legal issues rather than just the technical retrieval of data. Digital forensics personnel can be technicians who handle evidence gathering, policymakers who consider broader implications, or professionals with both technical and legal expertise. Professionals need skills like identifying relevant evidence, obtaining search warrants, recovering evidence using tools, and following forensic investigation processes.
The document discusses several legal, social, and ethical issues raised by the Internet of Things (IoT). Some of the key legal issues include data privacy and security concerns as IoT devices often have poor security and transmit data without encryption. Cybersecurity is also a major issue as IoT bots can be hacked and used to launch cyberattacks. On the social side, the proliferation of IoT devices risks increased global warming and climate change as more devices consume power. There are also privacy concerns if devices are hacked and personal information is stolen. In terms of solutions, the document advocates for improved government regulation of IoT, following ethical codes of conduct, prioritizing customer benefit, strengthening security, and raising customer awareness.
This document discusses reasons for disliking digital forensics and identifies areas for improvement. It begins by introducing the author's background and motivation. The document then examines issues with naming conventions, tools/practices, standards/definitions, training/certification, and subfields. Key problems highlighted include a lack of standardization, compatibility issues between tools, outdated mindsets, and insufficient computing foundations in training. The author advocates treating digital forensics as an engineering science and applying best computing practices. Overall, the document critically analyzes challenges currently facing the field and questions how these issues may impact the future if not addressed.
Cyberethics is the study of moral, legal, and social issues involving cybertechnology and its impact. Cybertechnology refers to computing and communications devices like computers, networks, and the Internet. The history of cyberethics includes four phases defined by the evolving technologies from standalone machines to today's converged technologies. While some argue cyberethics issues are not unique, others believe new issues have emerged due to the scale and scope enabled by cybertechnology, like the ability to stalk multiple victims globally without leaving home.
This chapter discusses computer and internet crime. It begins by outlining the objectives of understanding key ethical issues around data security, reasons for the rise in security incidents, common attack types, perpetrator objectives, and elements of a multilayer security process. It then discusses why incidents are so prevalent due to increasing complexity, user expectations, and reliance on commercial software with vulnerabilities. Common attack types like viruses, worms, Trojan horses, and phishing are also outlined. The chapter concludes by discussing prevention, detection, response, and establishing security policies and risk assessments to implement trustworthy computing.
Machine learning and the challenges of digital transformation in the lawSebastian Ko
The adoption of machine-learning (a form of artificial intelligence) by lawyers is shaping the future of law –as a profession and institution. Today, pockets of practice and traditional workflows have undergone massive transformation, viz. legal research and document reviews in discovery, regulatory disclosures, M&A, and contract management. Many alternative legal services providers, “legaltech” vendors, and other “NewLaw” businesses were born in the 2010s. Yet, truly full-service “robo-lawyers” are nowhere in sight. This seminar will examine –from a legaltech industry perspective– the technological influences on emerging industry trends, including the applications of analytics and natural language processing. The discussion will focus on how software encodes the law and legal processes in software, the related technological and ethical challenges, and the adoption barriers in legal practice.
This document discusses ethical issues related to information systems. It introduces the concept of NORA technology which can find obscure relationships in data from multiple sources, potentially violating privacy. It then outlines principles of ethics like responsibility, accountability, and liability. The document presents a 5-step process for ethical analysis and 6 candidate ethical principles. Professional codes of conduct and real-world dilemmas are discussed. The rest of the document focuses on privacy, outlining US privacy protections and fair information practices that are the basis for many privacy laws. The European data protection directive and US safe harbor framework in response are also summarized.
This document discusses various topics related to intellectual property, including copyrights, patents, trade secrets, plagiarism, reverse engineering, open source software, and cybersquatting. It provides an overview of these key concepts, including definitions, legal protections, limitations, and issues that arise. The objectives are to explain what intellectual property encompasses and why companies work to protect it, as well as discuss strategies, laws, and challenges regarding intellectual property rights in information technology.
The Innovation Gap: Why the Justice System Has Failed to Keep Pace with Techn...Robert Ambrogi
This was my keynote delivered to the Legal Services Corporation's 2018 Innovations in Tech Conference. Few would dispute that technology is one of the keys to addressing the justice gap. Yet at a time when technological innovation abounds, the justice gap grows only wider. The problem is not technology – it is the justice system’s failure to employ it. In this program, we’ll explore the impediments to broader use of technology and what can be done to overcome them.
October 29, 2019, I was invited to present the keynote of the LegalTech Alliance meeting on eDiscovery and Big Data, in which 11 law departments from the Universities of Applied Sciences in the Netherlands participate.
eDiscovery is more and more important than ever. Future legal professionals must be able to deal with large electronic data sets so they can:
- Take decisions based on facts and not based on guesses and assumptions;
- Answer information requests timely, accurately and complete;
- Avoid high cost, reputation damage, regulatory measures, business disruption and stress!
It is great that the LegalTech Alliance understands that need and that they embed eDiscovery in their educational programs.
Attached are slides of the workshop were we presented the course eDiscovery (including the hands-on with ZyLAB) which we developed together with the University of Applied Sciences in Amsterdam
This document defines open data and provides examples of its use. Open data is publicly available data that can be freely used, shared and built upon. Examples like Citymapper, Zillow and FlightAware demonstrate how open data from transportation, real estate and aviation has been used to build useful applications. The document discusses open data essentials, guidelines, formats, sources, challenges and how people can participate by contributing, advocating or finding innovative uses for open data.
Ai and applications in the legal domain studium generale maastricht 20191101jcscholtes
November 20, 2019, it was my great pleasure to present a special lecture on Artificial Intelligence and Application in the Legal Domain. In this lecture I discuss how the development of machines that can learn, reason and act intelligently – Artificial Intelligence (AI) – is advancing rapidly in the legal domain. In some areas, machine intelligence have even already surpassed the limits of what the brightest human minds are capable of achieving, especially in the field of eDiscovery and Legal Review of large data set.
In others, machines still struggle with seemingly basic tasks. Nonetheless, breakthroughs in AI already have profound impact on the legal profession. AI is set to improve our world now and will continue to do so in the future. At the same time, there is the fear of losing control.
This lecture was part of a larger series on AI organized by our department of data science and knowledge engineering: https://www.maastrichtuniversity.nl/events/artificial-intelligence.
More information can be found here: https://textmining.nu
Summary:
The Internet of Things has been touted as the centerpiece of many innovative devices as it grows to encompass nearly every type of product imaginable. Already, appliances, cars and even buildings are being equipped with the capability to access Wi-Fi and wired networks. This has led to new efficiencies and data-driven opportunities for enterprises across the board.
When you hear “the next big thing,” do you think they’re thinking big enough? Attend this webinar to find out more.
Presenter:
This webinar will be presented by Arthur Donkens, the managing partner of ITSX. Arthur has been active in information security since 1986, by advising, auditing and collaborating with more than 30 top class companies. Through his rich experience, he has been issued with credible certificates in information security, and has contributed in this sector by writing articles and whitepapers that are available. His moto is “Balancing security and business goals through well designed security architectures.”
Video here - https://www.youtube.com/watch?v=6fm_rzIL8gA
The Technology Committee of the Clinical Section continues its Webinar series on Tuesday with a webinar about CALS's A2J Author technology.
So you say you want to teach your students using experiential learning, expose them to technology worthy of modern law practice AND increase their awareness of the access to justice gap? With the Center for Computer-Assisted Legal Instruction’s (CALI) A2J Author, you can do this. A2J Author is a web-based tool that lets lawyers automate legal processes or court forms without having to learn to program. It has been used by legal aid and courts to automate over 1000 forms and processes and has been used by SRLs (self-representing litigants) over 3 1/2 million times ... and .... it's free for US law schools to use in their courses.
During the AALS Clinical Section Technology Committee’s upcoming Technology Tuesdays Webinar on March 14, from 4-5 p.m. EST, John Mayer, CALI's Executive Director will demo A2J Author and talk about how it has been used in legal education courses covering a variety of legal subject areas. A2J Author is also an ideal platform for rapid deployment of automation to assist in immigration and hackathon events. Come learn about CALI's best kept secret.
The document discusses technology and summarizes key points from a presentation on the topic. It begins by defining the term "geek" and discussing the need to understand one's audience. It then explains that a "black box" refers to something that can be understood based on its inputs, outputs, and functions without knowing its internal workings. The document summarizes views of business, applications, and technology from both top-down and bottom-up perspectives. It also discusses requirements, service management, cloud computing models, and provides a high-level look at potential future directions for IT.
Data is everywhere and in everything we do. Most of the time, usable information is hidden in raw data and because of that, there is an increasing demand for people capable of working creatively with it. To fully understand how we can assist data science workers to become more productive in their jobs, we first need to understand who they are, how they work, what are the skills they hold and lack, and which tools they need. In this paper, we present the results of the analysis of several interviews conducted with data scientists. Our research allowed us to conclude that the heterogeneity between these professionals is still understudied, which makes the development of methodologies and tools more challenging and error prone. The results of this research are particularly useful for both the scientific community and industry to propose adequate solutions for these professionals.
Digital forensics involves extracting evidence from digital devices like computers. This usually involves extracting and interpreting the contents and meaning of files. There has been growing interest in digital forensics courses across many academic disciplines. Some challenges include artificial limitations imposed by legal issues rather than just the technical retrieval of data. Digital forensics personnel can be technicians who handle evidence gathering, policymakers who consider broader implications, or professionals with both technical and legal expertise. Professionals need skills like identifying relevant evidence, obtaining search warrants, recovering evidence using tools, and following forensic investigation processes.
The document discusses several legal, social, and ethical issues raised by the Internet of Things (IoT). Some of the key legal issues include data privacy and security concerns as IoT devices often have poor security and transmit data without encryption. Cybersecurity is also a major issue as IoT bots can be hacked and used to launch cyberattacks. On the social side, the proliferation of IoT devices risks increased global warming and climate change as more devices consume power. There are also privacy concerns if devices are hacked and personal information is stolen. In terms of solutions, the document advocates for improved government regulation of IoT, following ethical codes of conduct, prioritizing customer benefit, strengthening security, and raising customer awareness.
This document discusses reasons for disliking digital forensics and identifies areas for improvement. It begins by introducing the author's background and motivation. The document then examines issues with naming conventions, tools/practices, standards/definitions, training/certification, and subfields. Key problems highlighted include a lack of standardization, compatibility issues between tools, outdated mindsets, and insufficient computing foundations in training. The author advocates treating digital forensics as an engineering science and applying best computing practices. Overall, the document critically analyzes challenges currently facing the field and questions how these issues may impact the future if not addressed.
The document discusses interoperability between government agencies and their IT systems. It states that for systems to effectively share information and for online services to work properly, all levels from legislation to running code need to use common vocabularies and definitions. It also discusses the different types of interoperability needed, including political, legal, organizational, semantic and technical. For information sharing and collaboration between agencies to work, their systems need to have common information models and exchange formats defined based on shared vocabularies. The document argues more analysis is needed of domains and collaboration complexity for successful interoperability rather than just viewing it as an IT problem. Semicolon activities aim to establish methodologies for improved interoperability.
Legal education of the future is information and technologyOmar Ha-Redeye
The document discusses how law schools need to adapt their curriculum to prepare students for the future of legal practice which will be heavily influenced by information technology. It argues current education focuses too much on traditional skills like legal research and writing but not enough on technical competencies. Lawyers need to understand tools like cloud computing to provide competent, cost-effective services to clients. While concerns about privacy and confidentiality are valid, reasonable precautions can allow use of these technologies. Overall, law schools must teach students how to create new legal approaches using innovative technologies, not just replicate past practice models.
Satya Pal has over 28 years of experience in the technology industry. He has worked with open source technologies to develop business applications, with a focus on platforms for publishing industries. These include workflow management, content delivery, and analytics tools. Satya has a M.Tech in computer science and M.Sc in physics. He has previously worked for several companies and currently serves as COO of Digiscape Tech Solutions, focusing on their platform business.
20120911 delija kukina - education of digital forensics expertsDamir Delija
This document discusses the need for continuous education in digital forensics. It notes that without training on tools and methodology, digital forensics work cannot be done effectively, especially from a legal standpoint. It outlines the different areas of expertise needed, including operating systems, hardware, applications, and networking. It emphasizes that knowledge in digital forensics is always evolving due to changes in technology and crime. Continuous learning, certification, and feedback from real-world experience are important to stay updated. Cooperation and simple internal organization can help overcome limited resources for training.
Visiting researcher lecture on AI legislation and smart governance at the Department of Middle Eastern Studies College of Humanities and Social Sciences, Hamad Bin Khalifa University.
12 March 2023
Data protection and privacy framework in the design of learning analytics sys...Tore Hoel
Presentation on The Influence of Data Protection and Privacy Frameworks on the Design of Learning Analytics Systems at LAK17, Vancouver, Canada - 2017-03-16
Digital ready policymaking and the digital screening process(1)PanagiotisKeramidis
This document outlines digital screening of policy initiatives by the European Commission to ensure they are digital-ready. It discusses screening policy initiatives across the entire policy cycle to identify how technology converges with legislation. The digital screening process involves assessing initiatives based on dimensions like EU priorities, interoperability, and legal environment. Over 400 initiatives have been screened, resulting in benefits like ex-ante evaluation and fostering interoperability and digital transformation among EU digital policies and standards. Future areas of focus include applying artificial intelligence and expanding the methodology to other thematic areas.
Trends in Law Practice Management – Calculating the RisksNicole Garton
Presented by the CBA’s Legal Profession Assistance Conference, the Canadian Lawyers Insurance Association and the National Law Practice Management and Technology Section live via webconference.
The advantages of cloud computing, virtual or online law practices and unbundling of legal services are getting a lot of press – convenience to clients, reduced overhead expenses, remote access, and enhanced access to justice are among the benefits touted. But there are also very real and practical risks, and ethical implications, for each new tool or practice implemented. As these trends infiltrate legal practice in North America, lawyers and law firm leaders need to exercise due diligence to assess the potential risks and benefits.
Our panelists, Nicole Garton-Jones and David Bilinsky will provide a practical overview of these trends in law practice management. In doing so, they’ll provide you with tools to reduce the risk and identify the questions you need to ask yourself, as well as potential third party service providers, your insurers and your law society, when conducting your own risk-benefit analysis.
Register here: http://www.cba.org/pd/details_en.aspx?id=na_onfeb212
This document discusses several ethical, social, and political issues raised by information systems. It addresses principles of responsibility, accountability, and liability regarding data use and privacy protection. Contemporary technologies like data mining and predictive modeling pose challenges to privacy and intellectual property. Laws and policies are still developing to address these issues.
The document discusses the DATAIA Institute, a convergence institute in France focused on data science, artificial intelligence, and their societal impacts. The institute brings together over 130 affiliated researchers from 14 academic institutions. It aims to address 4 overarching challenges: machine learning and AI, data and knowledge, transparency and ethics, and data protection. The institute will conduct research, training, and partnerships with industry on topics like responsible and transparent AI, algorithmic bias, and data privacy.
This document outlines a 10 step framework for developing data science applications. It begins with articulating the business problem and data questions. Next steps include developing a data acquisition and preparation strategy, exploring and formatting the data, defining the goal, and shortlisting techniques. Later steps evaluate constraints, establish evaluation criteria, fine tune algorithms, and plan for deployment and monitoring. The document also provides background on the speaker and organization. They offer data science, quant finance, and machine learning programs and consulting using Python, R, and MATLAB on their online sandbox platform.
This 3-credit professional practice course focuses on social and ethical issues related to computing. The objectives are to develop students' understanding of the historical, social, economic and professional responsibilities of the computing field. Students will analyze case studies on ethics and professionalism. The course covers topics like definitions of computing disciplines, professional societies, ethics, legal issues, security, and social responsibilities. The goal is for students to gain knowledge about important considerations for computing professionals.
Legal practice is all about information communication, use and management. The Digital Paradigm enables improved and efficient use of information systems to commoditise basic and repetitive advice common to many legal issues. Legal Expert Systems - a subset of Artificial Intelligence - provide further opportunities to develop advice giving processes and systems. This presentation will discuss how Legal Expert Systems can be deployed, how they can be created and their possible application beyond the law office and in the Court system, thus enhancing access to justice.
Taming Feral Systems With APIs in Region Östergötland’s Digitalisation PlatformNordic APIs
Caregivers often have many “unofficial” healthcare IT-related systems and a growing number of external apps that meet important business needs but have vulnerable management or limited (sometimes non-existent) integration that lead to double documentation and make coordination difficult. The phenomenon is called “feral systems”. Even for health care providers with a strategy of trying to collect patient data into a few centrally decided and managed systems, we believe it is better to find ways to “tame” the feral systems than to try to eradicate hunting. The lecture shows how we want to support businesses that see a need for tailor-made solutions for things that are not adequately addressed by the main systems, with the help of various parts of the Östergötland Digitalisation Platform (RÖD).
Computer Science is the study of computers and computational systems. Unlike electrical and computer engineers, computer scientists deal mostly with software and software systems; this includes their theory, design, development, and application.
e-SIDES workshop at BDV Meet-Up, Sofia 14/05/2018e-SIDES.eu
The following presentation was given at the workshop "Technology solutions for privacy issues: what is the best way forward?" organized by e-SIDES at the BDVe Meet-up in Sofia on May 14, 2018. The workshop, chaired by Gabriella Cattaneo from IDC, involved stakeholders from ICT-18 projects.
Bias in algorithmic decision-making: Standards, Algorithmic Literacy and Gove...Ansgar Koene
The document discusses bias in algorithmic decision-making and governance standards. It introduces Ansgar Koene and several projects aimed at addressing algorithmic bias, including developing an IEEE standard on algorithmic bias considerations and a governance framework for algorithmic accountability. It then discusses the concept of algorithmic literacy and the need for awareness raising, accountability standards for public sector algorithms, regulatory oversight, and global coordination on algorithm governance.
Similar to Towards Research-driven curricula for Law and Computer Science - Wyner and Partain (20)
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?Speck&Tech
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Towards Research-driven curricula for Law and Computer Science - Wyner and Partain
1. TOWARDS RESEARCH-DRIVEN
CURRICULA FOR LAW AND
COMPUTER SCIENCE
Dr AdamWyner
Department of Computing Science
University of Aberdeen
Dr Roy Partain
Law School
University of Aberdeen
BILETA Conference
University of Aberdeen
April 10, 2018
2. PROBLEM
• How can we develop curricula to equip law school/computer science students
with the skills to understand, critique, use, and develop legal technologies?
• The parameters for new curricula are broad and demanding:
• Various users for legal technologies, each with motivations and requirements
• Abundant legal information and powerful computational tools
• Novel roles to fill in the legal technologies sphere
• AI and Law research literature to design curricula and develop legal technologies.
• Is there a ‘line’ between professional training and training for research?
2
3. CONTEXT
• AI/Technology and Law
• Solicitors Regulation Authority and Bar Standards Board
• Dynamic context for government, judiciary, firms, law schools, public
• Intensive business development
3
4. SCOPE
• Law applied to ComputingTechnologies
• What the law says about: online privacy, autonomous vehicles, intellectual
property,…
• Computing technologies applied to law
• How can we apply computational tools to : case-based reasoning,
information extraction, argumentation, legal process management, contract
construction, …
4
6. ROLES
• Knowledge engineer – represent, process, and reason with legal knowledge
• Technologist – working with available tools (OPA, contracts, ODR, etc.)
• Process analyst – broker for subprocesses of a legal action
• Project manager – sees a complex process thorough
• Data scientist – mines and interprets data
• Risk manager – identifies and manages risk for contracts and compliance
• Others
(from Susskind, 2017)
6
7. COMPUTER SCIENCE BSC
• Computer programming and principles
• Computer architecture
• Web technology and application
development
• Object-oriented programming
• Mathematics for computing science
• Data management
• Human computer interaction
• Algorithmic problem solving
• Modern programming languages
• Operating systems
• Principles of software engineering
• Languages and computability
• Knowledge-based systems
• Robotics
• Distributed systems and security
7
8. WITHIN A TOPIC AREA - AI
• Problem-solving by search
• Multi-agent systems
• Logic
• Set theory
• Knowledge representation and reasoning
• Perception
• Planning
• Uncertainty – probabilistic,
argumentation
• Learning – observations, statistical,
reinforcement
• Natural language processing and
generation
8
9. COMPUTER SCIENCE CAREERS
• Software application developer
• Computer systems analyst
• Software systems developer
• Web developer
• Network systems administrator
• Database administrator
9
10. LLB
• Criminal law
• Legal system
• Legal method
• Legal theory
• Contract
• Public law and human rights
• Delict and unjustified enrichment
• EU Institutions and law
• The law of property
• Family law
• Succession and trusts
• Evidence
• Commercial and consumer contracts
10
Lots of articulation
within a topic area
12. MASH UP
• How to mix and match?
• How to do so without being too superficial in any one (or all) thing(s)?
12
13. LAW WITH COMPUTING SCIENCE
UNIV. OF ABERDEEN
• Year 1: 8 year one law + 2 level one computer science
• Year 2: 7 year two law + 2 level two computer science
• Year 3: 2 year three law + 3 level three computer science
• Year 4: dissertation
https://www.abdn.ac.uk/study/undergraduate/degree-programmes/1146/M1G1/bachelor-of-laws-
with-computing-science/
13
14. LLM LEGALTECH
SWANSEA UNIVERSITY
• AI and law
• Automating legal services
• Computational thinking for lawyers
• Quantitative analysis and big data
• Blockchain/distributed ledger technology
• Rights and accountability in the digital
economy
• Legal services in a digital world
• LegalTech entrepreneurship
• Digital intellectual property
http://www.swansea.ac.uk/postgraduate/taught/coming-soon/#legaltech-llm=is-expanded
14
15. OTHERS
• Python programming with some legal examples
• Georgetown
• Harvard
• Getting at the law or computer science?
• What can be done with this amount of programming?
15
16. PATCH
• Asking students to
• figure out the connections
• envision analyses and implementations
• implement
16
18. WHAT DO WE GET AT THE LEVELS?
• L1: Knowledge, comprehension, application
• Understand what a tool does and why
• Use/apply a tool
• Critique the strengths and weaknesses of a tool (needs information on possibilities)
• L2: Analysis, synthesis, evaluation
• Analyse given problems, systems, and tools
• Create novel computational tools and systems
• Determine the adequacy or appropriateness of a tool
18
19. LEGALTECH USE (L1) V.
COMPUTATIONAL ANALYSIS (L2)
• Analysing a problem from a computational point of view
• Algorithms – explicit sequence of processes from input to output
• Developing an algorithm leads one to decompose a large, complex
problem/task into smaller, implementable component parts.Then recompose
them into a larger solution.
• Prior to an implementation
• More generic, long-lasting, substantive than any implementation
• May lead to discoveries and a deeper understanding of a problem/issue
• Future proof intellectual skills
19
20. CAN V. OUGHT
• The problem, context, and spectrum of knowledge/skills require that
• while L1 can be done (teaching specific and practical knowledge/skills)
• L2 ought to be done (generic analysis skills for ongoing development)
• Distinction is already in legal and computer science training
• teach principles and topic areas
• not specific practices/techniques/tools
20
21. COLLABORATIONS IN SOFTWARE
ENGINEERING CYCLE
Requirements
analysis
Design
ImplementationEvaluation/testing
Evolution
What are the concepts,
problems, or issues?
How is something practiced?
What/where is the data?
What are the goals?
What is the reasoning?
What are the elements,
relations, and properties?
What are the actions?
What are the outcomes?
What is the algorithm or
logic?
Is the system working as
intended (right output)?
Are there errors/confusions?
How should it be changed?
What should be added?
21
22. LAW FROM A ‘SCIENTIFIC’ ANGLE
• The cycle applies a scientific method to legal information and practice
22
23. DYNAMIC CURRICULA
• Introductory level: programming, logic/math, algorithms, analysis, law, language
• Higher levels:
• project-based – pick a topic/problem to address
• collaborative work in teams – analysis and implementation are often larger
than one person.
• interdisciplinary – work/communicate across disciplines.
• modular – ongoing training/courses are sprints for understanding and skills.
Some ‘trails’ and some independent.
• Computer science practice
23
24. THANKS
• Adam Wyner – azwyner@abdn.ac.uk
• Roy Partain – roy.partain@abdn.ac.uk
24