Can Artificial Intelligence Applications Help Legal Professionals in the Lao Legal and Judicial Environment Similar to the United Kingdom?
By: Xaypaseuth Phomsoupha
Researcher & Author
This abridged article may be appropriate for Laotian legal practitioners, postgraduate students, and academic teaching staff in Lao universities.
I. Introduction
1.General
The legal profession traditionally involves meticulous research, extensive documentation, nuanced argumentation, and adjudication, which legal practitioners with artificial intelligence (AI) applications can now engage in.[1] Integrating AI into legal practice suggests streamlining operations, enhancing efficiency, and potentially regularising equal and equitable access to justice. People tend to believe that the potential benefits of employing algorithms to analyse contracts and make legal arguments and judicial decisions are forthcoming.[2] However, with evolving AI programs, especially those utilised in the legal sphere, machines tend to squeeze out the expertise of several paralegals, junior lawyers, and even court clerks, sparking concerns about allocative efficiency. AI helps humankind perform various legal obligations, such as contract review, legal research, enquiries, adjudication, and judicial review.[3] For the purpose of this paper, the author assumes that various computer programs such as ChatGPT, Gemini-Google’s AI Chatbot, Claude.ai and Copilot fall into AI-enhanced tools and that legal practice involves legal practitioners and judiciaries.
2. Intention
This paper was initially intended for academic purposes at a London-based university with which the author has long engaged. Acting as an alter ego of a legal practitioner in Laos, the author shortened his original version and made this article abridged and embedded with the Lao context for the Laotian audience. Although the novelty of AI may not be known to young and old lawyers of all generations, the author’s articulation in this paper should help legal professionals imagine the merits and constraints pertinent to its application in the Lao legal sector.
II. Emergence of AI
1.Understanding of AI-Enhanced Tools
In technical terms, AI is characterised by computer systems that can perform tasks that typically require human intelligence intervention.[4] Rule-based chatbots are, for instance, computer programs that operate on predefined rules and can only respond to specifics. The programs are advanced and use technologies like Natural Language Processing (NLP) and Machine Learning to understand the intent behind input information.[5] They can handle more complex queries and learn from past interactions to improve over time.[6] More advances include, without limitation, ChatGPT, Gemini-Google’s AI Chatbot, Claude.ai and Copilot, which legislation worldwide must underpin; the preceding tools operate on large language models storing a vast dataset of text and code.[7] One must understand that the main features of AI computer programs are based on rules, including but not limited to machine learning and deep learning, which contain substantial data fed by human action.[8] With the information publicly available to a machine or fed by a human operator, the machine can deliver outcomes derived from the machine learning process.[9] The deep learning process applies multi-programmed algorithms to evaluate data, whether number-based, descriptive, or imaginary, to generate results with passive or no human intervention. [10] With the designated algorithms, machines advise human participants on various legal matters as if the former had been natural lawyers.[11] Those machines impersonate human behaviours to provide specific outcomes for their users.
2.AI Applications in Legal Practice
AI refers to machine systems that mimic human intelligence in terms of program usage by legal professionals and perform tasks that would typically require human cognitive abilities.[12] Each language model listed under Section 1.1 above can help paralegals, clerks or even junior lawyers to deal with drafting legal documents quicker than they perform the tasks themselves. With AI-powered programs, legal professionals can interact with written conversations, meaning that the machines can understand the flow of a conversation on legal reasoning, remember previous arguments, and tailor their responses as the Parties used AI such as ChatGPT in Felicity Harber v The Commissioners for His Majesty’s Revenue and Customs.[13] The language programs can answer questions related to contracts, arbitration, and litigation, leveraging their knowledge base to provide informative and accurate responses.[14] Instead of legal assistants, computer programs can generate creative text formats, such as code, scripts, musical pieces, emails, letters, etc., and reasonably translate legal text between different languages.[15] So, legal practitioners utilise machine programs to help them perform tasks, including normative learning, interpretation, argument and counterargument establishment, problem-solving, and decision-making.[16] Beyond legal practice, machine programs are crucial for legislators in developing appropriate regulatory frameworks in certain jurisdictions.[17] Nowadays, AI has played a crucial role in helping adjudicators perform the duties assigned by their clients and voters in the democratic world.[18] People using AI must remain abreast to ensure that the law keeps pace with technological advancements and provides a clear and practical framework for governing its use in society.
3.Inequal Abiding by AI Rules
While the academia’s environment in many jurisdictions seems to be prejudiced against AI-assisted assignments students may have produced for submission, the legal sectors encourage legal practitioners, such as former law students, to adopt AI applications.[19] The author observes that academics may have used AI detection apps discretionarily to blame students for plagiarism, absent the extent to which succinct rules differentiate between teachers’ and students’ AI applications. The author argues against implicit inequality before the law of the two sectors functioning in a single jurisdiction, for instance, the UK. Recently, the UK government’s proposed AI definition in its draft legislation has sparked considerable controversy.[20] This lack of clarity could lead to confusion and uncertainty for businesses and regulators alike. Acknowledging people’s full rights to express their opinions, the author further suggests that the unsettled AI in the eye of the law should not persist in such advanced legislation in the UK.[21] As such, policymakers must balance promoting innovation and ensuring that AI is used safely and ethically.
III. Benefits and Risks Associated with the Adoption of AI-Enhanced Tools in Legal Practice
As introduced in Section 1 of this paper, people involved in legal practice have benefitted from and been evenly subjected to the risks of AI usage in their professional lives. The benefits and risks are not exhaustively presented below.
1.Benefits of AI Applications
With the advent of AI, the technology has made significant inroads into various sectors, including the legal profession. Various AI-enhanced programs promise to streamline processes, increase efficiency, and improve access to justice by virtue of online and physical arrangements.[22] The following aspects reflect the advantages of AI applications in legal practice:
(i) Streamlining Legal Research and Due Diligence. If completely done by human action, conducting legal research and due diligence are time-consuming tasks that involve analysing vast amounts of legal documents, case law, and statutory instruments, depending upon a lawyer’s experience.[23] With AI-powered legal research tools, legal practitioners and judiciaries can significantly speed up the process by automatically scanning, extracting, and interpreting relevant information from large databases as utilised in Comptroller v Emotional Perception AI.[24] These tools can identify relevant cases, statutes, and regulations, allowing legal professionals to access the information they need quickly, wherever and whenever required.[25] In Comptroller v Emotional Perception AI, Lord Justice Arnold agreed on the Appeal, in which the Appellant filed several claims, including “b) a database in which is stored a multiplicity of reference data files with content modality with target data and a stored association between each reference data file and related individual property vector. …within the trained artificial neural network ‘ANN’…, and each related individual property vector encoded the semantic description of its respective reference data file.”[26] AI can help with contract review and analysis, identifying key clauses, obligations, and potential risks. This can save legal professionals significant time and effort, allowing them to focus on more strategic tasks.
(ii) Improving efficiency and productivity. The computer programs are AI tools that can identify relevant cases, statutes, and regulations, allowing legal professionals to access the information they need speedily.[27] AI can help with contract review and analysis, identifying key clauses, obligations, and potential risks. With the assistance of computer programs, legal practitioners can save legal professionals significant time and effort, allowing them to focus on more strategic tasks.[28] Legal professionals can concentrate on complex and strategic legal assignments by automating routine tasks, increasing efficiency and productivity. However, productive proficiency outpaces allocative efficiency, considering equitable resource distribution.
(iii) Contract management. AI can streamline contract management and automation by automatically extracting critical information from contracts, tracking deadlines and obligations, and identifying potential risks and inconsistencies.[29] This helps lawyers manage contracts more efficiently, reduce the risk of errors and disputes, and ensure compliance with contractual obligations.[30] With the assistance of AI-power programs, many law firms increase their workloads without recruiting human legal resources. Moreover, limitations in some languages used to write the contracts are not readable by computer programs even though such AI-powered tools are up to date.
(iv) Innovation and Advantage. When law firms are equipped with AI-powered computer programs, lawyers working for the firms are likely to attain a significant advantage over other law businesses competing for the same work.[31] By frequently upgrading AI-powered tools and technologies, law firms can offer more efficient, cost-effective, and innovative legal services, attracting new clients and retaining existing ones.[32] AI can also help law firms stay ahead by identifying emerging legal trends and developing new service offerings to meet evolving client needs. In Hadleigh Cohen v The Commissioners for HM Revenue and Customs,[33] the Appellant filed to HMRC an appeal against a penalty under s 49(s) of the Tax Management Act 1970 due to confusion made by HMRC’s Webchat. With the assistance of computer programs to trace mistakes made by humans within the HMRC’s team, the appeal was agreed upon.[34] Judge Hunter Gill held, “[D]espite the confusion as to his obligations, we can accept that the Appellant’s actions were those of a prudent taxpayer exercising reasonable foresight and due diligence”.[35] Thanks to the innovation with which the Appellant’s legal team established arguments, the case could get through to the next stage of litigation.
(v) Enhancing Accuracy and Reducing Errors. AI can help reduce human errors in legal practice by using algorithm-based programs to perform tasks prone to mistakes.[36] The computer programs installed within the AI realm can help document review, ensuring all relevant clauses and provisions are identified and analysed, considering complicated cross-referencing amongst vast documents.[37] Equipped with AI-powered assistance, the legal teams of the Claimant and Defendant in Engineer AI Global Limited v APPY PIE LTD & LLP reviewed big chunks of relevant statutory instruments and contractual arrangements regarding intellectual property in arguing the case for their respective employers.[38] AI can help improve the quality of legal work with respect to inclusiveness and timeliness and reduce the risk of malpractice claims that may have resulted from inadvertence or misunderstanding by inexperienced legal practitioners. Moreover, AI can assist in identifying patterns and trends in legal quantitative data that are outside the capability of the legal sphere, enabling legal professionals to make more informed decisions and develop more effective legal strategies.[39] With automated non-human legal assistance, law firms and lawyers are more confident in providing flawless legal services for their clients.
(vi) Predicting Legal Outcomes and Adjudication Strategies. For people working in the judicial sphere, AI can help analyse vast amounts of legal data, including case laws for the legal professionals in the common law orbit, statutes, and court decisions, to predict legal outcomes and develop litigation strategies.[40] AI can assess the likelihood of success in a particular case, helping legal professionals make informed decisions about whether to pursue litigation.[41] Furthermore, AI can help identify potential weaknesses in the opposing party’s case, allowing legal professionals to develop more effective counterarguments. By leveraging AI’s predictive capabilities, legal professionals can improve their chances of success and achieve better outcomes for their clients.[42] Humanising the office equipment, legal professionals can suggest case outcomes for their clients within an appropriate time.
(vii) Improving Client Service and Satisfaction. While a law firm is by no means to act as a principal and the commercial AI-powered program as an agent, AI can help lawyers improve client service and satisfaction by providing faster and more efficient legal services.[43] With AI-powered tools, law firms and lawyers can respond instantly to client inquiries, offer all-clear day access to legal information, and automate the preparation of legal documents even during off-office hours.[44] AI can help personalise legal services, tailoring advice and recommendations to each client’s specific needs. By leveraging AI, legal professionals can provide a more responsive and client-centric approach to legal services, increasing client satisfaction and loyalty.[45] Having the Appeal approved by the Judges, the Appellant seemed to be content with the service rendered by its legal team.[46] Furthermore, AI can assist in identifying potential client needs and preferences, enabling legal professionals to proactively offer relevant legal services in the international arena by “[p]promoting interoperability with international regulatory frameworks”.[47] AI-enhanced programs generally help lawyers provide legal services for clients at a time and border-limitlessly.
2.Risks Associated with AI Applications
Artificial Intelligence (AI) is making significant inroads into various sectors, and the legal profession is no exception. Law firms and users must not overlook the risks of using AI-enhanced programs.
(i) Intellectual Property Issues. The rapid evolution of AI has led to intellectual property challenges in many jurisdictions. AI models, particularly those trained on vast datasets, often blur the lines of ownership.[48] If these datasets include copyrighted material, the AI-generated output can potentially infringe on existing rights. The question of who amongst the AI developer, the user providing data or the owner of the training data, owns the output further complicates the issue.[49] Furthermore, using AI to generate and store metadata poses another challenge that current patent laws struggle to address by making clear interpretations.[50] In Thaler v Comptroller,[51] Judges dismissed the appeal in a majority by not recognising the machines inventing AI-powered programs as the machine inventor was not a human. The unsettled legislation that should underpin the inventions of AI-generated programs can stifle innovation and deter investment in AI technologies to a great extent.
(ii) Inaccuracy and Bias. AI algorithms are trained on vast datasets, which may inadvertently provide inaccurate results due to misinterpreted inputs and input data per se. Such biased causation of input can proliferate adverse consequences with respect to legal interpretation when applied in legal practice.[52] An example is given in the instance that a disagreement emanates from the input word “transmitting” files used for the services from a server originating in the United States, which the laws of Japan mean “producing” a program in an output; different interpretations ended up in a court case.[53] Generally, an AI system trained on factual data wrongly fed by unidentifiable actors might perpetuate unsupportive claims, jeopardising a lawyer’s proposition for her clients.[54] Wrong data in a system results in undesired outcomes, which are analogous to Rodriguez’s statement, “[w]hen biased data is used to train machines to make decisions, and these biases can cause an application to act discriminately…” [55] In Hadleigh Cohen v The Commissioner,[56] HMRC’s Extra Support Team erred by notifying the appellant of the income tax payment deadline through its Webchat. In the first circuit of case proceedings, the Commissioner won the case. However, Judges Manyara N and Hunter G. approved the Appeal and set aside the penalty imposed. Under the foregoing circumstances, the AI users fully shoulder damages due to office automation.
(iii) Job Redundancy. The AI-enhanced tools potentially raise concerns about job displacement in the legal profession.[57] While AI can handle routine tasks like document review and legal research, it might also replace paralegals, legal assistants, and even some lawyers, as interpreted by several lawyers, including the author, in section 9(3) of Copy Right, Designs and Patents 1988,[58] leading to unemployment and economic disruption. The rise of AI-powered legal services might create a two-tiered system in which those who can afford sophisticated AI tools have a significant advantage over those who cannot, differentiating between developed countries, developing economies and marginalised groups.[59] Some scholars have raised questions about the replacement of human legal experts by machines.
(iv) Overreliance. The convenience and efficiency of AI might lead to an overreliance on nonchalant machines without human intervention, potentially undermining the critical thinking and analytical skills of legal professionals that must be avoided.[60] Lawyers might become overly dependent on AI-generated insights, neglecting to conduct their independent analysis or exercise professional judgment. Such overreliance can lead to deskilling and declining legal service quality.[61] Lawyers may not be too confident about having machine companions and then sack long-time legal assistants such as junior lawyers, paralegals, and secretaries because the principals lack empathy like computers.
(v) Ethical and Professional Responsibility. Using AI in legal practice raises significant ethical and professional responsibility concerns.[62] Lawyers may be compelled to perform duties and provide competent representation to their clients, and relying on AI systems without proper understanding or oversight can jeopardise this duty.[63] The use of AI in decision-making processes raises questions about accountability and responsibility. In Peter Marano v The Commissioners,[64] The appellant, Mr Marano, was liable for late submission of a tax return, per the UK legislation in 1970, resulting in a GBP 574,422.00 penalty payable to the Respondents. The Appellant’s counsel argued that automation built into the Respondent’s premises caused the late tax return submission; thereby, the Appellant should not have been held responsible. However, Asplin LJ, supported by Nugee LJ and Counsel LJ, dismissed the Appeal, ascertaining that the computer programs underpinned by applicable law were doing a good job.[65] The author wants to contend that the court tribunal’s decision is incorrect as the computer programs available may not be retroactively governed by the UK legislation of the 1970s. Furthermore, it is still arguable whether organisations or humans are accountable when an AI system makes an error or leads to an adverse outcome.
3.Criticisms of AI Applications in Legal Practice
(i) The risks listed by the author in this paper typify criticisms of the benefits that result from AI applications in legal practice. Both sides of the new technology may not be equally recognised by human actors in every jurisdiction around the globe.[66] One must note that legislation pertinent to IA is relatively fledgling in many jurisdictions, even in the UK, where the legal system is fully developed.[67] The technological innovation with the partial support of law is by no means achieving complete legitimacy, thereby leading to a double standard that people living under the same jurisdiction must abide by.[68] Social organisations operating across the international jurisdictional environment would suffer from (i) the distinctive advancement in AI innovation in each particular jurisdiction and (ii) the differentiation between national legislation and international law.[69] Ultimately, questions on whether the benefits surpass risks, or vice versa, are left unanswered in many places.
(ii) While legal practitioners and associates have appraised AI evolution and applications globally, the author further contends that many state court judges making decisions based on machine action are in due process in the eye of such relevant legislation; challenges akin to the author’s contention are found in Thaler v Comptroller.[70] The author argues that Lord Hodge unsupportively led and consolidated the judgments by dismissing the Appellant’s action to operate his machine to invent the computer programs with which services are provided for the Respondent.[71] The author further suggests an argument against the judgments from a reverse angle. In the event that the AI-power programs make errors resulting in financial damage to the Respondent, the Appellant will be liable for damages payable to the former on the grounds of the latter’s ownership over the machine. Otherwise, when human actors write textbooks and articles, their contributions are appropriately credited in the publishing. However, AI program owners are not credited for their work that contributed to AI-assisted judicial documents produced by state court judges and arbitration panels.[72] The author has found citations in many contemporary judgements containing the names of tribunal judges who heavily rely upon case analyses made by their machine companions, as in Emotional Perception AI Ltd v Comptroller.[73] Laymen of the judicial process may ask whomever the judges or AI programmers make judgments. When an AI program error occurs and results in ill advice to clients, no existing law makes clear that a lawyer user or programmer assumes vicarious liability to the aggrieved party. Likewise, using AI by plaintiffs, defendants, and judiciaries, the lawyer’s roles are diminished to the extent to which human legal representation should have been ousted by machine operation.
(iii) The other arguments the author wants to put forward here are works, such as contract drafting and motion and statement writing generated by AI-powered programs, which may not be considered a penultimate version. The task-lead lawyer herself needs to diligently double-check whether the computers make consistent arguments therein by reading the entire papers several times lest she be accountable for errors made by the computer programs, which operate under her guardianship. Under some jurisdictions outside the common law orbit where precedent court judgments are absent from the public domain, AI tends to admit that computer programs cannot search for precedents commanded by their users or owners. In many cases, lawyers may not advise clients to swear an oath before tribunals by explicitly referring to an AI-generated statement without a human lawyer to empathise with the surroundings inside and outside the courts. Ultimately, engaging AI compels lawyers to spend multiple times and resources to complete a single task. Likewise, commercial computer programs like ChatGPT, Gemini-Google’s AI Chatbot and Copilot are not liable for errors, whether in breach or tort, made by their using lawyers but leave contingent liability for law firms adopting the innovative computer programs instead of cost reduction.[74] One of the imminent threats is the clicking auto texts suggested by computer programs featuring in word processing when and if the lawyers do not reread the texts she has produced. Turner stated, “[t]he seller of a medical AI diagnostic program may exclude liability to a hospital buying the software for harm caused where the AI misdiagnoses a patient”.[75] Thus, the author is sceptical about whether AI algorithm-based programs can replace human intelligence in specific fields.
(iv) To sustain the legal sector in any jurisdiction, the author suggests that legislators must balance the actions of human lawyers and machine operations, for instance, as laid out in Practical Law IP&IT.[76] The author holds that the legal sector’s prosperity emanates from consistent coordination between AI inventors, users and lawmakers. One may contend whether innovative legal practice tools bring the highest efficiency when AI-powered program users are legally hindered by legislation, which varies from jurisdiction to jurisdiction within the AI network.
1.AI Applications
The advent of information technology, including various AI programs, has enabled humanoid teammates for legal practitioners and those working in the non-judicial and judicial areas.[77] People generally hold that this novel invention has progressively affected their lives. In contrast, many stakeholders in legal practice and the judicial sector have perceived the benefits and risks of AI usage.[78] The weight of either side varies from jurisdiction to jurisdiction.
2.On the Benefit Side
AI has helped legal people access innovative technology whereby machines can perform tasks better and more efficiently than humans.[79] The legal functions performed by AI in lieu of legal practitioners range from retrieving data to analysing legal instruments to reviewing contracts to interpreting cases or to providing desired results according to the purposes set by humans within a shorter time, with higher accuracy and more cost-effectiveness when compared with results from human action.[80] For those working in the judicial area, AI judges, court clerks, jurors, and other court personnel, with the assistance of AI programs, can search for precedents, produce records, and finalise judgments better than humans are supposed to do themselves.
3.On the Risk Side
One may blame the machines for the adversarial actions and outcomes of AI applications, which may be contrary to the benefits. These include inaccuracies resulting from the fed information or machine errors.[81] Machines may be unable to deliberate matters or empathise with clients’ opinions. Moreover, when lawyers and judicial crews rely too much on machine functionalities, legal human actors may be considered to ignore ethics while being obliged to hold clients accountable.[82] The downside of AI applications in legal practice depends on the jurisdiction under which results are applied to the users.
4.Author’s Final Words
(i) The author argues against the equality of AI acceptance by different sectors under the same jurisdiction. Judges are credited more than AI programmers when using AI programs for adjudication. The human lawyer’s role will linger because technologically advancing people, including plaintiffs, defendants, and adjudicators, appoint machines as their solicitors, rendering legal service. The question of who among IA programmers, judges, legal professionals, and IA users benefits more from technological invention remains unanswered from a legal perspective.
(ii) Irrespective of his role in the UK or Laos, the author has witnessed AI providing only productive efficiency. Nonetheless, AI has not allowed the author to attain allocative efficiency when AI rejects newly graduated law applicants for filling positions of junior lawyers and paralegals in the author’s law firm. In all cases, Lao legislation should be available and underpin AI applications in the commercial legal field and judicial sector.
BIBLIOGRAPHIES
Case Laws
Comptroller – General of Patents, Designs and Trademarks v Emotional Perception AI Limited, [2024] EWCA Civ 825
Emotional Perception AI Ltd v Comptroller-General of Patents, Designs and Trademarks [2023] EWHC 2948, Case No. CH-2022-000144
Engineer AI Global Limited v APPY PIE LTD & LLP [2024] EWHC 1430 (IPEC) [1]-[7]
Felicity Harber v The Commissioners for His Majesty’s Revenue and Customs [2023] UKFTT 01007 (TC)
Hadleigh Cohen v The Commissioners for HM Revenue and Customs [2024] UKFTT 00707 (TC)
Peter Marano v The Commissioners for His Majesty’s Revenue & Customs, [2024] EWCA Civ 876
Thaler v Comptroller-General of Patents, Designs and Trademarks, [2023] UKSC 49 [2021] EWCA Civ 1374
Legislation
Copyright, Designs and Patents Act 1988, s. 9(3)
Online Safety Act 2023, >O>OH-ON>
UK Parliament Acts, Online Safety Act 2023
AI Toolkit (UK), Practical Law UK Toolkits 2024
Books
Siegel E., Predictive Analytics, (Willy & Sons, Inc., 2016)
Susskind R., and Susskind D., The Future of Professions: How technology will transform the work of human experts (Oxford University Press, updated edition 2022)
Turner J., Robot Rules: Regulating Artificial Intelligence (Palgrave MacMillan 2019)
Articles
Amalia Diurni and Giovani Ricco, “ChatGPT: Challenges and Legal Issues in Advanced Conversational AI” [2023] 9 Italian LJ 473
Andrea Radonjanin,” Regulating IP aspects of generative AI: any lessons to be drawn from the past?” [2024] European Intellectual Property Review, Volume 46, Issue 6, 236-335
Arisa Ikeda, Akito Honda, Kensuka Yamamoto and John A. Tessensohn, “Grand Panel of IP High Court of Japan established cross-border patent infringement liability for computer-implemented invention”, [2024] European Intellectual Property Review, Volume 46, Issue 3
Charles Kerrigan, “Artificial intelligence and equity”, [2017] LexisNexis JIBFL 430 (7)
Chris Kemp and Richard Kemp, “Legal aspects of AI (UK”, [2024] Thomson Reuter, Practical Law UK Practice Note w-018-2338
Dominique Garingan and Alison Jane Pickard, “Artificial Intelligence in Legal Practice: Exploring Theoretical Frameworks for Algorithmic Literacy in the Legal Information Profession, [2021] LexisNexis Legal Information Management, Volume 21, Issue 2
Duc Tran, “The UK government’s approach to regulating AI – a lighter touch”, [2022] Privacy and Data Protection, Vol 23, Issue 2
Ed Walters, “AI: Practice, Not Promise, in Law Firms”, [2019] Law Practice 45 Law Practice 42
Gianluca Campus, “Generative AI: main copyright issues and some (partial answers in the EU AI Act” [2022] European Intellectual Property Review, Volume 46, Issue 7
Lee Bell,” Machine Learning Versus AI: what’s the difference?” [2016]
LexisNexis, “How to manage the risks of artificial intelligence in your business?”
Maggie Boden, “On Deep Learning, Artificial Neural Networks, Artificial Life, and Good Old-Fashioned AI” [2016]
Pablo J.O. Rodriguez, “Artificial Intelligence Law: Applications, Risks & Opportunities” [2021] Volume 90 REV. Jur. U.P.R. 701 (2021)
Practical Law Dispute Resolution, “Artificial intelligence in dispute resolution toolkit”, [2024] Thomson Reuter, Practical Law UK Toolkit w-042-1299
Practical Law EU, “Regulation laying down harmonised rules on artificial intelligence”, [2024] Artificial Intelligence Act: legislation tracker, Thomson Reuters
Practical Law IP&IT, “AI: UK regulatory developments”, [2024] Practical Law UK Practice Note w-040-5421, 11, Thomson Reuters
Sandy Tsakiridi, “The draft Act: the good, the bad and ugly”, LexisNexis, [2022] Privacy and Data Protection, Volume 22 Issue 3
Sugam Sharma and Dava Prasad, “Emerging Legal Informatics Towards Innovation: Current Status and Future Challenges and Opportunities”, [2021] LexisNexis Legal Information Management, Volume 21, Issue 4
[1] Richard Susskind and Daniel Susskind, The Future of Professions: How technology will transform the work of human experts (Oxford University Press, updated edition 2022) 84-88
[2] AI Toolkit (UK), Practical Law UK Toolkits w-035-7209, 1-2
[3] Practical Law IP&IT, AI: UK regulatory developments, [2024] Practical Law UK Practice Note w-040-5421, 11, Thomson Reuters
[4] Jacob Turner, Robot Rules: Regulating Artificial Intelligence (Palgrave MacMillan 2019) 7-28; 5
[5] Eric Siegel, Predictive Analytics, (Willy & Sons, Inc., 2016) 210-221
[6] Ibid, 227-231
[7] ibid (n 3) 11; Practical Law EU, “Regulation laying down harmonised rules on artificial intelligence”, [2024] Artificial Intelligence Act: legislation tracker, Thomson Reuters
[8] Sandy Tsakiridi, “The draft Act: the good, the bad and ugly’, LexisNexis, [2022] Privacy and Data Protection, Volume 22 Issue 3, 14-15
[9] Lee Bell,” Machine Learning Versus AI: what’s the difference?” [2016] paras 4-5
[10] Maggie Boden, “On Deep Learning, Artificial Neural Networks, Artificial Life, and Good Old-Fashioned AI” [2016] para 2
[11] ibid
[12] Thaler v Comptroller-General of Patents, Designs and Trademarks, [2023] UKSC 49 [2021] EWCA Civ 1374, [2], [99]
[13] Felicity Harber v The Commissioners for His Majesty’s Revenue and Customs [2023] UKFTT 01007 (TC) [3]-[13]
[14] ibid
[15] ibid
[16] ibid (n 12) [2], [99]
[17] Practical Law EU, “Regulation laying down harmonised rules on artificial intelligence”, [2024] Artificial Intelligence Act: legislation tracker, Thomson Reuters
[18] UK Parliament Acts, Online Safety Act 2023, LexisNexis 2023, Pt 12, c 50
[19] Ibid (n 4) 81-103
[20] ibid (n 18) c 50
[21] ibid (n 8) 14-15
[22] ibid (n 2) 1-2
[23] Chris Kemp and Richard Kemp, “Legal aspects of AI (UK”, [2024] Thomson Reuter, Practical Law UK Practice Note w-018-2338, 4-5
[24] Comptroller – General of Patents, Designs and Trademarks v Emotional Perception AI Limited, [2024] EWCA Civ 825 [1]-[7]
[25] ibid [37-[53]
[26] Ibid, Appendix Claim 1 b)
[27] Practical Law Dispute Resolution, “Artificial intelligence in dispute resolution toolkit”, [2024] Thomson Reuter, Practical Law UK Toolkit w-042-1299, 3-4.
[28] ibid (n 23) 19
[29] Ibid 19-20
[30] ibid (n 3) 1-2
[31] ibid (n 8) 14
[32] ibid
[33] Hadleigh Cohen v The Commissioners for HM Revenue and Customs [2024] UKFTT 00707 (TC) [5]-[16]
[34] Ibid [100]
[35] Ibid [99]
[36] Ibid (n 4) 22-28
[37] Engineer AI Global limited v APPY PIE LTD & LLP [2024] EWHC 1430 (IPEC) [1]-[7]
[38] Ibid [8]-[13], [18]-[22]
[39] Duc Tran, “The UK government’s approach to regulating AI – a lighter touch”, [2022] Privacy and Data Protection, Vol 23, Issue 2, 14-15
[40], ibid (n 30) 1-2
[41] Ibid 3
[42] ibid (n 24) [54]-[55]
[43] Ibid (n 4) 42-47
[44] ibid (n 3) 2-3
[45] Emotional Perception AI Ltd v Comptroller-General of Patents, Designs and Trademarks [2023] EWHC 2948, Case No. CH-2022-000144 [15]-[18]
[46] Ibid [84],
[47] ibid (n 3) 4
[48] Gianluca Campus, “Generative AI: main copyright issues and some (partial answers in the EU AI Act” [2022] European Intellectual Property Review, Volume 46, Issue 7, 343-447, 1-3
[49] Andrea Radonjanin,” Regulating IP aspects of generative AI: any lessons to be drawn from the past?” [2024] European Intellectual Property Review, Volume 46, Issue 6, 236-335, 6-8
[50] Online Safety Act 2023, >O>OH-ON> c 50, pt 12 ss 226-241
[51] Thaler v Comptroller-General of Patents, Designs and Trademarks, [2023] UKSC 49 [2021] EWCA Civ 1374, [2], [91] – [99]
[52] Arisa Ikeda, Akito Honda, Kensuka Yamamoto and John A. Tessensohn, “Grand Panel of IP High Court of Japan established cross-border patent infringement liability for computer-implemented invention”, [2024] European Intellectual Property Review, Volume 46, Issue 3, 191-196, 2
[53] Ibid 2
[54] ibid
[55] Pablo J.O. Rodriguez, “Artificial Intelligence Law: Applications, Risks & Opportunities” [2021] Volume 90 REV. Jur. U.P.R. 701 (2021), p. 708
[56] ibid (n 33) [1]-[100], [101]
[57] Ed Walters, “AI: Practice, Not Promise, in Law Firms”, [2019] Law Practice 45 Law Practice 42, 4
[58] Copy Right, Designs and Patents Act 1988, s. 9(3)
[59] ibid (n 49) 2
[60] LexisNexis, “How to manage the risks of artificial intelligence in your business?” 9
[61] Ibid 4-8
[62] Amalia Diurni and Giovani Ricco, “ChatGPT: Challenges and Legal Issues in Advanced Conversational AI” [2023] 9 Italian LJ 473, 491-494
[63] ibid (n 8) 14
[64] Peter Marano v The Commissioners for His Majesty’s Revenue & Customs, [2024] EWCA Civ 876 [2]
[65] Ibid [20] – [22], [47]
[66] ibid (n 8) 14-16
[67] ibid (n 39) 15-16
[68] ibid (n 59) 6-8
[69] Dominique Garingan and Alison Jane Pickard, “Artificial Intelligence in Legal Practice: Exploring Theoretical Frameworks for Algorithmic Literacy in the Legal Information Profession, [2021] LexisNexis Legal Information Management, Volume 21, Issue 2, 97-99
[70] ibid (n 12) [2], [91] – [99
[71] Ibid [1] – [4], [99]
[72] ibid (n 45) [15]-[18]
[73] ibid
[74] Ibid (n 4) 81-103
[75] Ibid 106
[76] Sugam Sharma and Dava Prasad, “Emerging Legal Informatics Towards Innovation: Current Status and Future Challenges and Opportunities”, [2021] LexisNexis Legal Information Management, Volume 21, Issue 4, 226-230
[77] ibid (n 1) 84-88; ibid (n 69) 97-99
[78] ibid (n 3) 11Ibid (n 4) 7-28; 5
[79] ibid (n 24) [1]-[7]
[80] ibid (n 27) 3-4; ibid (n 33) [5]-[16
[81] Ibid (n 52) 191-196, 2
[82] ibid (n 64) [2]; Charles Kerrigan, “Artificial intelligence and equity”, [2017] LexisNexis JIBFL 430 (7)