preparing georgia stakeholders for the ai...

Preparing Georgia Stakeholders for the AI

RevolutionDaniel Schiff

September 5, 2019

Georgia Institute of Technology, School of Public PolicySTIP Program, Enterprise Innovation Institute

Outline• Significance of AI • Defining AI

• Research Question• Methods

• Findings• Map of AI Policy Strategies• Key Policy Sectors• Key Social/Ethical Barriers to Innovation• Deep Dive: Labor Displacement

• Creating an AI Strategy

Presenter

Presentation Notes

Personal story Want you to come out knowing what it is, why it matters, and what you can do about it

Significance of AI

• Major breakthroughs circa 2012• AI as “Fourth Industrial Revolution”

• Massive economic development potential• Rebranding of “Big Five”

• But – social, ethical, legal, and policy concerns

Presenter

Presentation Notes

How do approach sustainable AI innovation? Economic development WEF, UN, OECD

What is Artificial Intelligence?

AI: A DefinitionArtificial intelligence refers to a set of statistical techniques

applied to certain domains of computer science and

implemented across social and economic systems, which

has the potential to improve or harm human and environmental well-being

Human and global well-

being

Economic and social systems

Domains of computer science

Statistical techniques

Presenter

Presentation Notes

As common as regression to machine learning Speech and image recognition, decision-making systems. Alexa or Siri Self-driving cars to Amazon’s targeted advertising to Google search. Also virtual chatbots for customer service, making recommendations about prison sentences to cancer diagnosis. Enhance or substitute for human intelligence. Ability to adapt and ‘learn’ without human control, hence autonomous augments and supplements human cognition, and We DO have control over how they’re designed, implemented, and regulated

Research Question

How are governments, corporations, and non-profits strategizing around AI:

- economic development potential?

- policy sectors most impacted?

- barriers and risks?

Presenter

Presentation Notes

The speed these docs have been created is staggering. These orgs are taking this issue very seriously, so we should pay attention and can learn from them. How do they approach sustainable AI innovation? What strategies are they proposing to maximize AI’s innovative potential while minimizing social and economic risks?

MethodologyManual coding of 60+ AI policy strategy documents

Identification of themes

Presenter

Presentation Notes

Point out orgs are writing AI policy strategy docs. Define them. Starting largely in 2016… Governments (e.g., US, China, India, EU) Corporations (e.g., Google, Microsoft, Intel, Baidu) Non-profits (e.g., IEEE, ACM, Japanese Society for AI, academic, military think tanks) Coded 100xx documents, over 3000 pages with a team of 4 coders Coded for 24 social/ethical topics: Inequality, labor disruption, economic impacts, human rights, etc. 14 policy sectors: Transportation, healthcare, agriculture, criminal justice, etc. In the last month, docs from: G20, OECD, Russia, and the White House Office of Science and Technology Policy, Australia

Consultations/Interviews

● Bogdana Rakova, Samsung and Accenture

● Ana Marušić, University of Split, Croatia

● Virginia Dignum, European Commission High-Level Expert Group on Artificial Intelligence

● Jason Borenstein, GA Tech

● Justin Biddle, GA Tech

● Kelly Laas, Illinois Institute of Technology

Findings

Presenter

Presentation Notes

Proliferating in G7 countries

Key Policy Sectors for GA Stakeholders

● Employment & Workplace○ OECD: Governments should take steps, including through social dialogue,

to ensure a fair transition for workers as AI is deployed, such as through training programmes along the working life, support for those affected by displacement, and access to new opportunities in the labour market.

● Education, Training, & Skills○ UK: Expand the skills section in the Industrial Strategy to include the

development of problem-solving, creativity, interpersonal, and adaptability skills - as these group of skills are those that humans have a long-term competitive advantage in.

● Governance, Regulation, & Law○ France: [AI] necessitates the development of procedures, tools and

methods which will allow us to audit these systems in order to evaluate their conformity to our legal and ethical frameworks.

Key Social & Ethical Concerns for GA Stakeholders

● Privacy, Surveillance, & Data Governance○ India: Data is one of the primary drivers of AI solutions.... Challenges include

data usage without consent, risk of identification of individuals through data, data selection bias and the resulting discrimination of AI models, and asymmetry in data aggregation.

● Transparency & Open Data○ Montreal Declaration: In accordance with the transparency requirement for

public decisions, the code for decision-making algorithms used by public authorities must be accessible to all.

● Inequality, Bias, & Discrimination○ SAP: Bias can negatively impact AI software and, in turn, individuals and our

customers. This is particularly the case when there is a risk of causing discrimination or of unjustly impacting underrepresented groups.

Deep Dive: Labor Displacement Challenges

● World Bank: 57% of OECD jobs at risk● Brookings: 44.7% of ‘tasks’ in Greater Atlanta ~ 2.7 million jobs

● Organization for Economic Cooperation and Development:○ Repetitive manual tasks: production, agriculture, food, transportation○ Repetitive cognitive tasks: paralegals, accountants, cancer diagnosis○ Regions with low-wage earners, men, racial/ethnic minorities○ Less vulnerable: women, health care, education, “pink-collar” jobs

● McKinsey Global Institute:○ Potential for net job gains WITH aggressive government policy○ Growth: professionals, care providers, managers, educators

Presenter

Presentation Notes

Overall, the study finds that 14% of jobs across 32 countries are highly vulnerable, defined as having at least a 70% chance of automation. A further 32% were slightly less imperilled, with a probability between 50% and 70%.

Deep Dive: Labor Displacement Recommendations

● China: K-12 education, STEM, competing for talent

● UK: Focus on problem-solving, creativity, interpersonal, and adaptability skills to complement AI

● Intel: Up-skilling and the re-skilling of the workforce, particularly in job areas that are less likely to be automated

● Microsoft: Lifelong learning & re-training; worker transition / social safety net

● India: Industry-education partnerships; creation of new jobs

Presenter

Presentation Notes

Georgia’s High Demand Career Initiative Report. Useful to look at, pretty good list of job priorities. BUT no mention of AI or automation. U.S spends among the lowest in the world on labor market policies

Recommendation: Create an AI Strategy

Do You Need an AI Strategy?

● Local governments: “With the pervasive emergence of artificial intelligence technologies, state lawmakers have been more nimble than their Congressional counterparts in staking state prominence —and competition among each other — in a rapidly evolving field of economic development.”

- John Haughey, FiscalNote (17 Issues Facing State Legislatures in 2019)

● Corporations: “A data strategy alone is rarely enough. I therefore recommend every company has a separate AI strategy.”

– Bernard Marr, Forbes (How To Develop An Artificial Intelligence Strategy: 9 Things Every Business Must Include)

Presenter

Presentation Notes

2017 MIT Sloan Management Review: only 5% companies have extensively incorporated AI; less than 40% have an AI strategy in place. Lack of IT infrastructure

https://www.bernardmarr.com/default.asp?contentID=1843

Creating an AI Strategy

1. Identify key purpose & audience

2. Designate lead and recruit stakeholders

3. Review AI strategies from similar organizations

4. Consider challenges specific to your policy sector

5. Key ethics concerns

6. Key economic development concerns

7. Develop short- and long-term SMART goals

8. Establish process for measurement and ongoing evaluation

Presenter

Presentation Notes

Identify key purpose & audience Develop an initial AI innovation strategy for a small org? Develop a code of ethics for an org already using AI? Determine which AI services a gov might use? Creating a local resource center, incentives, grants for small businesses. Tie to your business or government strategy, but may want to even reevaluate that Smarter products/services, more intelligent business processes, automating repetitive tasks Designate lead and recruit stakeholders for committee Someone with technical know-how, understands organization’s work. Relevant stakeholders – different agencies, public, customers. Can recruit academic, business partners, etc. Multi-sector, participatory documents generally higher quality Review AI strategies from similar organizations Small, large, gov, corporate What technologies, skills, capacity do you need? What’s feasible? Implementation/change management. Consider talking to someone from one of those orgs Consider challenges specific to your policy sector What policy domains? What social/ethical concerns do they emphasize? What recs? Labor displacement and training; privacy and data security; and avoiding AI products/services that reinforce bias or otherwise harm people. Legal issues, perception by public, media, conusmers Key ethics concerns: bias, privacy, Key econ development concerns: labor displacement Develop short- and long-term SMART goals (Specific, Measurable, Attainable, Relevant and Timely) So these are not generic, but actionable Short term to set ground work and infrastructure Establish process for measurement and re-evaluation Moving target, needs to be an iterative process. Not one and done. Establish follow-up process as part of the plan, including any monitoring bodies, etc. https://www.forbes.com/sites/bernardmarr/2019/03/19/how-to-develop-an-artificial-intelligence-strategy-9-things-every-business-must-include/#727f40a18360 http://www.ncsl.org/research/telecommunications-and-information-technology/artificial-intelligence-the-future-is-here.aspx https://www.bernardmarr.com/default.asp?contentID=1844 https://www.bernardmarr.com/default.asp?contentID=1843

Creating an AI Strategy: Toolkit● Accenture – Fairness Tool

○ Assess algorithmic fairness and bias○ https://www.accenture.com/gb-en/blogs/blogs-cogx-tackling-

challenge-ethics-ai

● Bernard Marr & Co. – AI Strategy Template○ Help develop AI strategy○ https://www.bernardmarr.com/default.asp?contentID=1843

● DCMS – Data Ethics Framework and Data Ethics Workbook○ Evaluates data use in public sector against framework○ https://www.gov.uk/government/publications/data-ethics-

framework/data-ethics-framework○ https://www.gov.uk/government/publications/data-ethics-

workbook/data-ethics-workbook

● Dot Everyone – Responsible Technology Product Management Toolkit○ Development cycle assessment toolkit○ https://doteveryone.org.uk/building-a-responsible-tech-model/

● Institute for the Future and Omidyar Networks –Ethical OS Toolkit○ Evaluate risks and implement ethical solutions○ https://ethicalos.org/

● Information Accountability Foundation – Big Data Assessment Framework and Worksheet○ Assessment framework for policy and governance○ https://drive.google.com/file/d/0B5VI8fwlCQPkRFduSEVwM2Zl

Nnc/view

● Open Data Institute – Data Ethics Canvas ○ Identify ethical issues related to a data project○ https://theodi.org/article/data-ethics-canvas/

● RAEng – Diversity and Inclusion Progression Framework○ Assessment of diversity and inclusion efforts○ https://www.raeng.org.uk/publications/other/diversity-

progression-framework

Daniel [email protected]

Thank you!

https://www.accenture.com/gb-en/blogs/blogs-cogx-tackling-challenge-ethics-ai

https://www.bernardmarr.com/default.asp?contentID=1843

https://www.gov.uk/government/publications/data-ethics-framework/data-ethics-framework

https://www.gov.uk/government/publications/data-ethics-workbook/data-ethics-workbook

https://doteveryone.org.uk/building-a-responsible-tech-model/

https://ethicalos.org/

https://drive.google.com/file/d/0B5VI8fwlCQPkRFduSEVwM2ZlNnc/view

https://theodi.org/article/data-ethics-canvas/

https://www.raeng.org.uk/publications/other/diversity-progression-framework

mailto:[email protected]

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