Artificial Intelligence and the Future of Work in Social Enterprises

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Today in London, our Ogunte #ImpactWomen #GoodBreakfast audience wanted to know more about Machine Learning (ML) and Artificial Intelligence (AI), the truth, the misconceptions, and how we can use them in our social enterprises, and shape the future of work. Here’s the summary of our session, packed with resources!

This session was hosted and animated by:

1. First a bit of myth debunking

It’s important to explore what Machine Learning and Artificial Intelligence are really about, and what they can and can’t do.

“Artificial intelligence is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and other animals. In computer science AI research is defined as the study of “intelligent agents”: any device that perceives its environment and takes actions that maximize its chance of successfully achieving its goals”

Read about the fascinating history of Artificial Intelligence starting in Antiquity.

Then have a look at this A to Z cheat sheet about the terms that are frequently used and misused on the topic.

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2. There is Weak AI and Strong AI

AI is not limited to a story of robots. That would be a pretty simplistic way to describe what it is…

There's "weak AI"

So let’s distinguish Weak AI (very narrow, what Artificial Intelligence is today), an Artificial Intelligence which is specifically programmed and focused to execute a narrow task effectively. For instance: only facial recognition or only internet searches or only driving a car.

We are far from taking over the world!

There might be some AI applications coming together and solve big problems, however we are not there yet…

The Future of Life Institute (a volunteer-run research and outreach organisation in the Boston area that works to mitigate existential risks facing humanity, particularly existential risks from advanced artificial intelligence) says that to have a realistic time line about the developments in AI, you need to at least double your time expectations to see any substantial developments.

And then there is “strong AI”

The main vision is to develop Artificial Intelligence to the point where the machine’s intellectual capability is functionally equal to a human’s.

We can see efforts in applications wishing to mimic humans. Yet we are not talking about mimicking the way humans think and do.

“Humans are not necessarily a superior species. It’s our ability to deal with complexity that is interesting and using tech to augment this, is useful. However we need to be very mindful to the decisions we make,” says our guest Karen Rivoire.

What about algorithms?

An algorithm is a list of rules to follow in order to solve a problem. Algorithms need to have their steps in the right order to work properly.

They also depend on the information input. If it is biased, the output will be biased too.

We have handed over decisions to algorithms we wouldn’t have let go off in the past.

As technology develops, our host Karen insisted there is still time to influence the development of the technology, but we need to get involved now. Our knowledge of communities, our proximity, our connections, are of key importance.

At the moment some organisations are using technology to research and solve issues in health, science, energy consumption and more, such as Deep Mind (acquired by Google in 2014).

One of Deep Mind’s approaches is to use AI to deliver better care for conditions that affect millions of people worldwide.

3. So what do I do first?

  • Remember that an algorithm is a programme. We can not programme human brains into 1s and 0s. THE PROGRAMMING doesn’t solve the problem.
  • Start with understanding your own data. Does it fit your purpose?
  • Audit your organizational processes, what needs to be more mindful, where you need more evidence, more automation, more learning. Look at your values, your identity, your emotional intelligence (how you develop it how you use it) and how inclusive you are in your operations and impact.
  • Remember that your expertise in social innovation, and your purpose-led work is as important as technology.
  • Your input and actions need to be personalised and fair but only with great customer insight and coherence.
  • Finally, technology (good data and analytics) can reinforce value-driven leadership.

Karen advocates using the P.A.I.R. methodology

  • Purposeful
  • Adaptive
  • Intersectional/Inclusive,
  • Resilient

and to encourage staff and stakeholders to immerse themselves into a life-long learning mindset.

Questions samples:

  • How am I protective of my own data?
  • How much do I know about the data I have in house?
  • What do I want to learn?
  • How can I best use data to serve the participants in my purpose-led organization?
  • How does it help me to work towards a positive and intersectional social impact?

 

4. Explore the AI protocol.

Robbie Stamp, Chief Executive of Bioss International (working around judgment and decision making), gives an overview of the Bioss AI Protocol in this video.

Think about your Artificial Intelligence systems…

- Is the work they are doing Advisory? Does it inform your judgement? Is the decision eventually made by humans.

- Has the AI been granted Authority over any human being?

- Have you granted the AI Agency? Can it commit resources without human intervention? (Like in the Stock Exchange, or agency to machines to write code or repair their own code…)

- Application: are we clear when we abdicate responsibility to a machine… (eg a driverless car making decisions whilst you are doing something else and not paying attention to the core task as you’ve abdicated responsibility)

- Accountability: all humans have some sense of responsibility (albeit imperfect!). Artificial Intelligence cannot be accountable in the way humans currently are. Can it ever be?

5. Immerse yourself in AI world through powerful connections and reading

Hoover on the names to open links

Inspirational Women (What would we do without them… )

Cathy O’Neil : Mathbabe.org Weapons of Math Destruction.

Catherine Helen O'Neil is an American mathematician and the author of the blog mathbabe.org and several books on data science, including Weapons of Math Destruction. Some AI stuff has been created without basic Math foundations nor statistical ground. Cathy challenges this.

Kate CrawfordKate is a leading researcher, academic and author who has spent the last decade studying the social implications of data systems, machine learning and artificial intelligence. "We programme codes with huge bias in". Kate challenges that.

Joanna Bryson - Polymath psychologist and computer scientist. Associate Professor in the Department of Computing at the University of Bath, Joanna works on Artificial Intelligence, ethics and collaborative cognition. She asks: How to use tech to become even more human?

Tabitha Goldstaub - Co Founder of CognitionX, a market intelligence platform for all things artificial intelligence, enabling people and companies to educate themselves and get community led recommendations on how to deploy AI. Let's build AI with equality at its core, she says.

Martine Rothblatt The founder of Sirius XM satellite radio, Martine Rothblatt now heads up a drug company that makes life-saving medicines for rare diseases (including one drug that saved her own daughter’s life). Meanwhile she is working to preserve the consciousness of the woman she loves in a digital file … and a companion robot.

Networks:

TechSheCan: a diverse range of organisations who believe that together we will make a much greater impact to address the root cause of the problem.

AiforGood Artificial Intelligence for Global Sustainable Development

TeensinAI exists to increase diversity and inclusion in artificial intelligence

Reading:

Exponential View newsletter: Azeem Azhar’s wondermissive on technology, the future & society.

Tim o’Reilly: What’s the future and Why it’s up to us

The Benefits and Risks of Artificial Intelligence

Pete Trainor: An author, applied Artificial Intelligence designer, technologist, accidental polymath, mental health campaigner and co-founder of Us Ai. He talks all over the world on creative & social technologies, data, Ai and the physiological & psychological effects on their audiences.

Read Futureheads’ Be Kaler’s write-up on the hype / trust issues around AI.

Read OECD’s white papers on the Future of Work, and the list breakdown of routine and non routine jobs that will stay or go in the near future.

Read also this guide from CRAMS (a Health and Safety Software Solution) on how AI could help revolutionise healthcare.

Events to watch:

·  Internet Freedom Festival- Valencia, Spain- Yearly event every March.

·  RightsCon  Yearly event following Internet Freedom Festival

·  Royal Society of Arts (RSA) and DeepMind on The role of Citizens in Developing Ethical AI

·  Get a nano degree at General Assembly and explore learning at Udacity’s School of AI


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