I remember writing about AI adoption at the federal level some time last summer. A discouraging time for our team as AI adoption was near non-existent for both Canadian business and the private sector.
Even after more than a year of the tech being available at that time, Canadian organizations, both public and private, were having a real hard time adopting the technology. The barriers of AI adoption for Canada were made very apparent by institutes studying our marred acclimation towards the tech.
But I trudged on, believing that although Canadians were slow to adopt, when we finally made the leap, it would be a big one, and one to admire. With that being said, I am very proud of the milestones we've achieved in the Ontario transit industry adopting AI.
Bringing the 1st AI voice agent to life for Niagara transit has been an exciting journey to say the least - can't wait for more.
But seeing that the federal government still trying to figure out simple text chatbots does bring those feelings of malaise back to the surface. This is taking quite a long time. I understand that things in the public sector tend to move slower than others. But even so, in the time that AI has been around, our team, amongst many other teams, have determined that text-based chatbots do not yield the same experience with users, as do voice agents. A conclusion that might be harder to reach with slower implementations and testing of various generative AI channels.
Having someone to call on the phone will trump a message into an AI terminal every time. In addition, these agents carry much more human nuance and generally have much higher cooperation rates. The real challenge with AI adoption is recognizing that our human experiences are the most important part of any system or operation. How we perceive AI will determine how we adopt and use it.
I do urge the federal government to be more pro-active in its adoption of this technology. It has been a life changing experience for myself, my team, and we hope to be able to make Canadian lives a bit easier as we deploy more agents across both private and public landscapes.
So If your team is still trying to figure out how to implement AI within your organization, while minimizing hallucinations or 'errors' as the not so familiar will call them, feel free to schedule a discovery call with us.
There are now millions of use cases across all industries and sectors, it's just a matter of aligning those use cases, and tools, with your vision. While also engineering prompts in a way that generates consistent quality responses.
We are here to help.
Alex, Peak Demand
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A summary of the article is included below.
Link to Original Article: https://www.cbc.ca/news/politics/federal-civil-service-ai-chatbot-1.7277623
Summary: Canada's federal public service is embarking on an ambitious AI strategy aimed at enhancing government services by integrating generative AI technologies such as chatbots. Drawing inspiration from private-sector applications, the initiative seeks to streamline processes like Employment Insurance, Old Age Security, and immigration while addressing the challenges of managing extensive government data. As departments are encouraged to experiment with various AI solutions, the strategy emphasizes the importance of updating privacy legislation and ensuring accountability, particularly if AI systems provide inaccurate information. With an anticipated launch next March, the plan reflects a balanced approach to innovation, aiming to harness AI's potential while mitigating its risks.
Strategic Initiative: The federal government is developing an AI strategy to integrate generative AI into public service operations.
Chatbots as a Core Application: AI-powered chatbots are expected to play a significant role in assisting with government services.
Inspired by Private Sector: The strategy leverages private-sector successes in using AI for improved customer service and data management.
Data Management Enhancement: AI tools are seen as a solution to help civil servants navigate and manage vast amounts of government data.
Experimental Approach: Departments will be encouraged to experiment with different AI applications to identify the most effective solutions.
Implementation Timeline: The AI strategy is slated for a launch next March, with ongoing planning in the interim.
Privacy and Legislative Concerns: There is a recognized need to update privacy laws to address risks associated with the use of generative AI.
Accountability Issues: Ensuring accountability for potential misinformation from AI systems is a key challenge.
Balancing Innovation with Caution: The strategy aims to harness AI's benefits while mitigating ethical, legal, and operational risks.
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