Trusted AI starts with trusted data. 

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Leveraging case studies from business and regulatory perspectives this workshop showcases the tangible repercussions of not thinking through the implications of AI driven systems at scale throughout their development.

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It aligns attendees how to monetize data responsibly within their organizations. and attendees leave with a new understanding of their role in AI as data leaders, new perspectives and an actionable toolset that extends their role in their organizations by giving them new tools to innovate more responsibly when creating new AI driven products and services.

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Key Objectives

1. Equip Data Leaders with case studies about the repercussions of ‘irresponsible innovation’

2. Align, inspire and orient Data Leaders around a new vision for their roles and responsibilities as it relates to development of trusted AI.

3. Lay down a strong foundation with a strategy and operating principles for ethical AI

4. Establish the basis for a more co-creational, collaborative and responsible AI culture 

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Aspects of these workshops can be adjusted to fit your unique organizational needs, knowledge and experience levels. 

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Typical participants: Chief Data Officers, SVP, VP, Director and data team leads

Business Leaders fund and oversee the development of AI products. They must understand how to ensure successful release of AI products by surfacing and mitigating issues that lead to negative outcomes such as increased risk or exposure to bad actors, adverse brand reputation, low to no return on investment, declines in number of clients. This workshop takes leaders through a series of case studies and interactive experiences to help them understand what they can do to ensure a successful launch of their AI product.

 

• Understand risks and pitfalls (i.e. brand reputation, risk, trust, client counts, ROI, key data science talent quitting out of frustration) of AI/ML products on organizational goals (i.e. increase purchases, client #s, engagement, sales/revenues) via case studies. 

• Understand the role of communication and timing in mitigation of issues. 

• Ensure success of AI projects by developing tactics to communicate with data scientists and AI developers to mitigate risks early. Tactics include techniques to surface ethical issues early, quickly, and frequently through allotment of time in agile processes, budgets and time (e.g. release dates).

Using case studies and experiences that put them in the shoes of those they might affect, AI creators will be able to build less biased, more inclusive ML/AI products that work toward the betterment of individuals and society.

 

By workshop's end, they will:

• Understand impact of data driven products – especially AI/ML products and services

• Develop empathy for people affected by their product through a series of experiences designed to provide details that can only be known by experiencing a day in the life of the affected people: including per diem spending habits, interactions & access to technology and transit types, housing, and their daily obstacles for a better life as well as their overarching concerns.

• Develop strategies and tactics to reduce harmful impacts to affected people: including personal and organizational levers

• Leverage tools to help them assess impact of each new AI project