lucas colantoni Archives - IPOsgoode

Taking care of creatives in the digital age: A semester at Canadian Heritage

ccraig — Thu, 12 Dec 2019 23:08:41 +0000

As a student enrolled in the IP Intensive at Osgoode, I had the opportunity to intern at the (PCH) this semester. PCH is a department of the Government of Canada. Its mandate is centered on fostering and promoting “”. To achieve this mandate the department collaborates with a number of different stakeholders and engages with Canadians through a wide range of programs that foster Canadian cultural preservation and expression.

During my placement I worked exclusively for the Broadcasting, Copyright and Creative Marketplace Branch (BCCM Branch) of PCH. The BCCM Branch is responsible for supporting marketplace conditions for Canada’s cultural sector. The Branch is split up into a number of different teams, each with their own responsibilities. As an intern I worked within the Marketplace and Legislative Policy (MLP) team. The MLP team advises on the cultural sector’s legislative responsibilities for broadcasting and copyright. This includes providing advice on how these frameworks can be adapted to better serve creators, creative industries, and Canadians in general. The MLP team also houses the Lab on Data, Skills and Technology (the Lab). The Lab is responsible for furthering the Department’s thinking on the impact that emerging technologies like AI and blockchain have – and will continue to have – on creatives and the creative sector.

During my first week as an intern at PCH the writ dropped. My placement spanned the entirety of the Federal election and came to an end just before the new cabinet was sworn in. As I soon learned, Federal government departments have very specific guidelines to follow during an election period. Although departments are not prohibited from making decisions or announcements, they are required to exercise restraint and fulfill their responsibilities in a non-partisan manner.

A lot of the work that was going on at PCH while I was there involved updating briefing materials and other tasks related to preparing for the new government to form. My primary work product during my placement was a research project. In my final week as an intern I had the opportunity to present my research in front of my colleagues at PCH, and colleagues from the Canadian Intellectual Property Office (CIPO) and Innovation, Science and Economic Development Canada (ISED). In addition to working on my research project, I provided research support to my colleagues and had the opportunity to sit in on a number of different meetings and attend various presentations.

Many of the presentations and meetings I attended centred around innovation and the impact that digital technologies are having on the Canadian copyright system. One example that sticks out in my mind is the panel I attended on Artificial Intelligence (AI). What really hit home for me in that presentation is how rapidly technologies like AI can change the entire landscape of copyright in Canada. Policy makers have to anticipate how new technology like AI might impact society moving forward in order to respond in as timely a manner as possible. Accumulating and analyzing good data is critical to these efforts. Without good data, crafting balanced and effective policy is an extremely difficult task.

Overall, I greatly enjoyed my experience working as an intern at PCH. In general, my placement allowed me to gain a sense of what it’s like to work as a policy analyst for the Federal government. My colleagues truly made me feel like I was a valuable member of their team and never hesitated to provide me with constructive feedback on my work. There’s an open-door policy at PCH which made me feel comfortable going to my colleagues for advice and guidance. Having spent 10 weeks interning there it comes as no surprise to me why it was voted as one of Canada’s top 100 employers. From top to bottom PCH is filled with people that genuinely care about the well-being of their fellow colleagues.

I strongly encourage any student at Osgoode who is interested in intellectual property and technology law to apply to the IP Intensive. It is easily one of the most memorable and rewarding experiences I have had as a law student.

Written by Lucas Colantoni, Osgoode JD Candidate, enrolled in Professors D’Agostino and Vaver 2019/2020 IP & Technology Law Intensive Program at Osgoode Hall Law School. As part of the program requirements, students were asked to write a reflective blog on their internship experience.

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AI job recruiting: A law student’s OCI nightmare?

ccraig — Thu, 14 Nov 2019 01:46:12 +0000

There’s no shortage of commentary on the brokenness of the On-Campus Interview (OCI) process. It can be stressful, confusing, and many students – for whatever reason – come out of the process without having secured a job. Having gone through the process myself, I can confirm that even lawyers and law firm recruiters will tell you that there has to be a better way to hire. That said, can artificial intelligence (AI) potentially improve this process?

In recent years a lot has been made about the impact that AI can have on different areas, including job recruitment. Hiring can be expensive. have put the cost of hiring a new employee at roughly $250,000 USD [1]. With the ever-increasing data companies are accumulating on their hiring processes and employees, AI is being looked at as a tool that could lower the costs of hiring and improve hiring efficiency [2]. This all sounds great, right? Unfortunately, AI has the potential to be just as biased during the hiring process as humans are. AI hiring tools are trained by humans, typically using data sets from the real world. Training AI using data that reflects your current workforce can expose the fact that hiring managers have given preference to certain types of candidates over others []. One example is the AI recruiting tool that Amazon developed in 2014 to hire engineers. As soon as the , it started discriminating against women []. The data that the AI was being trained on was based on existing engineers in the Amazon workforce []. Due to hiring biases, this workforce was disproportionately comprised of males []. As a result, the AI recruiting tool was favouring male candidates over female candidates based on gender alone.

As this example demonstrates, the issue of selection bias is particularly impactful when AI recruitment tools are deployed in typically white male dominated fields, like law. This brings me back to the OCI process.�� I mentioned that the process is broken, one of the major reasons why is because members of minority groups []. In theory, AI tools should be able to mitigate this issue. However, the Amazon example shows us that the AI system you’re implementing will only be as good as the data you use to train it.

Large corporations like Amazon have the resources and market power to gain access to high quality data and have still managed to run into data-related issues with their AI. What chance do smaller players in the AI industry have for filtering out low-quality data when they train their AI, if corporate giants aren’t always successful at it? If Canada wants to foster innovation and combat AI bias, we need to promote quality data. One way that this goal could be accomplished is by introducing a Text and Data Mining (TDM) exception into the Copyright Act. As Prof. Pina D’Agostino noted in her to the Standing Committee on Industry, Science and Technology, a TDM exception would allow data to be mined for AI training purposes, and provide Canadian stakeholders with the legal clarity they need to access quality data that can be used to develop their AI [].

The application of AI to law student recruitment highlights the potential for AI to affect our lives in ways we may not anticipate. Law students, as soon to be lawyers, are in a unique position to impact how AI is regulated moving forward. The future direction of AI will affect all of us, not just students interested in IP. It’s important to think about how AI interacts with the law, and how the law may need to adapt in order to effectively regulate AI. For example, is a TDM exception the right approach or would another approach be better?

At the risk of sounding too preachy, I think AI is something all law students should be informed about. Even if you’re not a law student, AI will have an increasingly direct impact on your everyday life moving forward. The more you know about it, the better equipped you’ll be to adapt and respond to it. In recent years IP Osgoode has been at the forefront of educating the legal community on the challenges posed by AI through their [9]. I encourage you to read over the conference proceedings as it’s a great way to learn about AI from some of the foremost experts on AI in Canada and abroad.

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Written by Lucas Colantoni, Osgoode JD Candidate, enrolled in Professors D’Agostino and Vaver 2019/2020 IP & Technology Law Intensive Program at Osgoode Hall Law School. As part of the course requirements, students were asked to write a blog on a topic of their choice.

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[1] Rudina Seseri, “How AI Is Changing The Game For Recruiting” Forbes (29 January 2018), online: .

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[2] Ibid.

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[3] Aaron Holmes, “AI could be the key to ending discrimination in hiring, but experts warn it can be just as biased as humans” Business Insider (8 October 2018), online: .

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[4] Jonathan Penney, Address (Why is Data so Important to the Development of AI?, presentation delivered at Osgoode Hall Law School, 91��ɫ, Toronto, 21 March 2019), online:.

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[5] Ibid.

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[6] Ibid.

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[7] Jane Gerster, “Reality check: Does name-blind hiring help improve diversity>” Global News (17 July 2018), online: .

[8] Pina d’Agostino, “Submission to the Standing Committee on Industry, Science and Technology for the Statutory Review of the Copyright Act” (IP Osgoode, 2018), online:

[9] Osgoode Hall Law School, “Bracing for Impact: The Artificial Intelligence Challenge” (2018 and 2019), online: Osgoode Hall Law School .

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