Artificial intelligence (AI) is bringing an array of opportunities and challenges to businesses. Not least of these new changes is legal risk.
DX Journal spoke with Carole Piovesan, Litigator and Team Lead on AI, Privacy, Cybersecurity and Data Management group at McCarthy Tetrault, to find out how AI will affect businesses, who should be addressing the legal risks AI poses to society and how the legal practice itself is being affected by AI.
DX Journal: To what extent does AI pose a legal risk to enterprises looking to incorporate this technology?
Carole Piovesan: Since there’s a lot of talk about AI, let me start with a very short definition. AI is an umbrella term that encompasses different processes such as natural language processing (like Siri), image recognition, machine learning and deep learning. The “AI” that draws a lot of attention these days – both negative and positive – is usually machine learning and deep learning, both of which involve self-teaching and self-executing systems.
AI offers a lot of opportunity for businesses looking to improve efficiencies and cut costs. Depending on the purpose of the system, however, it can present certain legal risks.
For instance, AI systems require lots of data to train systems on how to accurately perform a certain task. Access to data is largely governed by the Personal Information Protection and Electronic Documents Act which sets parameters for how to legally access, store and use data, among other things. Companies need to understand how to comply with privacy legislation to avoid reprimand or sanction. In addition, amassing huge quantities of data could lead to competition issues around data monopolies, among other things.
Then there is the issue of liability where a system does something it shouldn’t have done or doesn’t do something it should have done. In self-teaching and self-executing systems, questions arise as to who should bear liability for harm caused by the system. This leads to the corollary issue of proof. The pathway to a particular output for these systems is notoriously difficult to understand.
There is a whole movement around increasing the interpretability of AI systems, particularly where systems are used in matters that directly affect human life such as medical diagnosis and criminal law.
DX Journal: Which industries are likely to be most affected by the legal risks that AI brings to businesses?
Piovesan: I wouldn’t think of it as industries that will be most affected by AI, but tasks. Every industry has the potential to be affected by advanced technologies including deep learning systems. The idea is that AI systems can perform routine, repetitive tasks better, faster and cheaper than humans. Every industry has processes that are repetitive in nature and that can be improved by AI.
That said, in the near-term, industries that are expected to be deeply affected by AI include transportation, medicine, law, insurance, accounting, manufacturing, retail, financial services, among others. Sectors that are less obvious but that are benefitting from AI include oil and gas, and mineral extraction, in which AI is being used to more safely and efficiently extract natural resources.
DX Journal: What should businesses focus on as they begin to onboard AI tools?
Piovesan: Depending on the purpose and complexity of the technology, business will want to develop a better understanding of AI technologies, as well as risk management strategies for incorporating more sophisticated technologies into their operations. Increasingly we’re seeing an interest in creating legal assessment tools specific to AI technologies.
DX Journal: Who is addressing the legal risks created by AI in society?
Piovesan: Many different actors have a role to play in ensuring safe, beneficial and productive innovation. I would say that provincial and federal governments need to kick-start a dialogue with the academic and private sectors around issues specific to AI technology. One critical area for greater discussion is with respect to the interpretability of AI systems, and requirements for explainability for systems used with direct impact on human rights and well-being.
The EU and UK are examples of jurisdictions that are undergoing regular consultations to inform a possible regulatory framework on AI. Canada has also done such consultations but I think more is needed.
The academic and private sectors are tasked with advancing innovation but, as we have seen with the 2017 Asilomar principles, for example, they can also lead in defining appropriate standards and codes of conduct to promote responsible and productive research and innovation.
Canada is well-situated in the AI field. Some of the foundational thought-leaders of deep learning are based in Canada. We have tremendous academic talent here.
Plus, the federal government announced $125 million in research and development focused AI and nearly $1 billion over 5 years to promote innovation superclusters.
These announcements made international headlines which is important to show the world that Canada is the place to be for research and innovation (not to mention we are known for having the second largest tech sector outside Silicon Valley).
Finally, Canada is a well-respected international player and AI is technology will require a coordinated international approach, especially with respect to data sharing and in the military and defence contexts. Canada is very well placed to add-value to any international dialogue on AI.
DX Journal: How is AI changing the legal practice itself?
Piovesan: AI presents tremendous opportunity in the legal profession. As lawyer become more exposed to and comfortable with the technology, we will increasingly incorporate AI into all aspects of our practice.
The law firm can use AI to streamline internal processes such as mandate scoping. By understanding how much a typical piece of legal work costs, law firms can more quickly and accurately estimate new work that is similar in scope.
At my firm, McCarthy Tétrault, we’re using AI in M&A due diligence work. In so doing, we’re able to complete due diligence for an M&A transaction in a fraction of time and for a fraction of traditional costs.
AI is also being introduced on the litigation side through systems that can complete legal research of concepts. It is also being used in e-discovery to increasingly categorize documents and predict relevance.
Canada uses blockchain to make research grants more transparent
The Canadian government has begun trialling blockchain technology as a way to improve the transparency of research grants. The National Research Council (NRC) is currently using an Ethereum-based system to publish funding information in real-time.
In a blog post, the NRC explained how blockchain technology could help to make government contracts more transparent. The blockchain’s public ledger means data recorded on the system is unalterable and open to everyone. This provides transparency into the workings of government, which in turn promotes trust.
Public-private partnership to drive pilot
To implement the trial project, the NRC has partnered with Canadian blockchain SME Bitaccess. It’s also working with the Industrial Research Assistant Program (IRAP), a body that generates a large volume of transactions each year and which would benefit from improved transparency.
Using funding from the Build in Canada Innovation Program, the NRC and Bitaccess are piloting a blockchain record-keeping system for the IRAP’s financial activities.
The program is part of the Canadian government’s wider efforts to improve transparency and utilize modern technologies. The NRC will be responsible for investigating how the blockchain could be applied to other areas of government. If the pilot proves successful, Canada could begin using blockchain more broadly to preserve public records and maintain transparency.
The trial is described as the first “real-use case” of its kind for deploying blockchain tech inside public institutions. The NRC said it expects to acquire “constructive” insights into how blockchain could be used by government bodies. Many tech visionaries see blockchain as crucial to the future of business but it’s still a new concept to most official organisations.
“These are early days yet, but the experiment is expected to provide constructive insight into the potential for blockchain technology and how it may be used for more open and transparent function of public programs,” said the NRC. “This experiment also marks an important step forward for the technology and a commitment by the Government to support emerging Canadian innovation.”
From cryptos to conservation
The blockchain is currently best known as the infrastructure supporting cryptocurrencies such as Bitcoin. In this scenario, the blockchain records every transaction on a decentralised public ledger. As the blockchain is immutable and distributed across computers around the world, the data stored within is always secured against external tampering.
These qualities are also what makes the blockchain concept attractive to organisations that need to store data transparently. The Canadian government’s initiative is just one example of how the tech could be used. Other recent blockchain-based projects have included schemes aimed at sports fans and unsustainable practices in the tuna industry.
Publicis Groupe partners with Microsoft to build new AI platform for 80,000 employees
Publicis Groupe has announced it is partnering with Microsoft to create a “disruptive” AI platform to digitally transform its operations. The organization will define the platform’s architecture, with Microsoft then providing the tech to build it.
Called Marcel, Publicis Groupe intends the AI-powered network to achieve three main aims:
- Curation of insights
- Providing employees access to these insights
- Connecting staff to boost problem solving.
Together, these tasks aim to deliver efficiency improvements to the company’s internal operations. Publicis Groupe currently employs more than 80,000 people who will use the new platform to connect with each other and organize information.
How it works:
Marcel will curate Publicis Groupe’s collective knowledge acquired through its business operations. This information will then be available to employees, allowing workers to access all the insights harvested by the company.
For example, an employee looking for info in one business might be shown an insight that was originally created in another operation. If it’s relevant to the task, Marcel will still present the data to the employee.
Marcel will also make individual connections between all 80,000 Publicis Groupe staff. This is intended to let employees access relevant support resources as and when they need them. As soon as a staff member encounters a problem, they could use Marcel to find an employee capable of providing immediate assistance.
Marcel to run on Azure
The platform is a sizeable initiative that Publicis Groupe believes will transform the way it operates. The design of the system is already being readied for Microsoft to implement using its cloud resources and AI capabilities. Marcel will run on Microsoft’s Azure cloud network with integrations into Office 365 for business insights.
“Marcel is a crucial step in Publicis Groupe’s commitment to radically change our industry, for the good of our clients and our people,” said Arthur Sadoun, Chairman and CEO of Publicis Groupe. “It’s why we’re thrilled to be able to draw on Microsoft’s ground-breaking talent, capabilities and resources in artificial intelligence, to build the platform of the future, today.
Publicis Groupe has been preparing Marcel’s architecture for several months. It first unveiled the platform last year while it was still in the design phase. The appointment of Microsoft as the project’s technical partner means Publicis Groupe is now progressing towards the introduction of Marcel to its employees and clients.
How Canada’s new digital service for government is approaching culture change
The digital transformation of organizations begins with an internal cultural shift promoting agile strategies, a hunger for innovative practices and the ability to change direction quickly.
As serial entrepreneur James Bilefield pointed out in an interview with McKinsey, culture change can be the biggest challenge of any major organizational shift:
“In my experience, culture is the hardest part of the organization to change. Shifting technology, finding the right talent, finding the right product set and strategy—that’s all doable, not easy, but doable. Hardest is the cultural transformation in businesses that have very deep legacy and cultural roots.”
That all seems taxing enough. Now imagine the organization in question has more than 100 departments and 250,000 employees. That’s exactly the challenge that the Canadian Digital Service (CDS) is facing.
CDS is a team working within the Treasury Board Secretariat to help the government design and build better services. Structured on the delivery of useful tools, the team is also helping government departments to build greater capacity for digital problem solving. The CDS team retains control of their communication tools allowing for their work to be shown out in the open. And through the government’s Interchange Program, they’re able to recruit private sector talent on short-term assignments.
Pascale Elvas, Director of CDS, has an up-close view of the government’s hunger for change and how many roadblocks there are along the way.
“We’re trying to get departments thinking about digital differently,” says Elvas. “We want them to really understand their users, the citizens that they serve and to unpack the problem.“
Traditionally, the government puts out a request for proposal (RFP) — the average size of the RFP and bids related to it is 8,000 pages long — detailing its requirements, a solution and asking vendors to build that solution. However, this traditional method is far from agile project development.
“By the time it’s deployed, it’s already obsolete and there’s no room for course corrections along the way,” says Elvas. “We’re trying to get departments thinking about digital differently. We want them to really understand their users, the citizens that they serve and to unpack the problem.”
Since Elvas joined CDS a year ago, the organization has grown from three people to 45, they get more than 40 requests from departments per month, and they’re recruiting just to keep up with demand.
Elvas says a change in perspective within government departments is at the root of the work being done by CDS:
“It’s getting departments thinking about digital in a different way, and not necessarily starting with an end-state solution from the outset. So allowing the discovery work to happen, to talk to real users along the way, to iterate and to adapt and course correct based on the insights gained through that work.”
Elvas and her team at CDS are advocating for whole new methods of addressing and carrying out projects, reworking the culture around tasks within the government, in order to put the needs of the citizen at the forefront.
“Part of this work is about culture change: It’s about breaking building projects down into smaller chunks, it’s about building microservices, it’s about using different methods, it’s about moving away from waterfalls to agile, it’s about active prototyping and constant iteration, moving to user needs over government needs, and iterating along the way based on user feedback.”
CDS follows the efforts made by both the Government Digital Service in the U.K. and the United States Digital Service to transform government in the 21st century. While everyone can agree that governments around the world need to revolutionize their use of digital tools to improve user experiences, the way forward can often appear muddy at best.
In one ongoing project, Natural Resources Canada (NRCan) is using CDS to open up data on household energy use in a transparent and reusable way. The initiative is particularly insightful as an early CDS project, as it involves working with legacy database systems, and includes user research sourced from various, unique data sets — specifically, provincial and municipal governments.
The expectations NRCan approached the project with, the kind of solution they already had in mind, changed radically after working with CDS to address the problem with a user-based mindset.
“When NRCan came to us,” says Elvas, “they came to us with a very specific solution in mind. NRCan wanted us to build them a database. They already had an internal database, so they wanted a database that was searchable by the public and that was more of a client-facing version of their internal database.”
“Now in doing the discovery work and talking to department officials and understanding their business, we discovered that what they were asking for wasn’t exactly what they needed. Building an API will enable all kinds of new services to be built and for private sector partners to use the data to do all kinds of other neat things — and open the door for much deeper service redesign work.”
CDS is hoping they can build on the success of projects like the API for NRCan to get government departments to reassess how they approach digital problem solving.
“We hope that by demonstrating an alternative way of doing things, we’ll move away from the traditional waterfall approach of launching an 8,000 page RFP with set requirements to really using service design and other methods to unpack the problem, understand the users and to build smaller solutions that can be iterated along the way.”
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