Business Ethics and Artificial Intelligence 2018

What it was:

CIPR written briefing studied as part of Continuous Professional Development, 27 February 2018:
Source: https://www.ibe.org.uk/userassets/briefings/ibe_briefing_58_business_ethics_and_artificial_intelligence.pdf

What I learned:

AI is relevant to Business Ethics – for example, how do you ensure your organisation’s values are being applied if decisions are being made algorithmically?

Potential risks of AI:

  • Ethics risk
  • Workforce risk (loss of jobs /skills)
  • Technology risk (cyber-attacks)
  • Algorithmic risk (biased decisions)
  • Legal risk (privacy / GDPR)

AIs may be accurate but nonetheless reflect human biases.

Open-sourcing may be important for openness and trust in AI systems – this could be especially true in Govt where trust is critical and keep source closed is less important.

“Explainability” is key to AI trust and to working alongside an AI partner.

AI work and contracts should specify responsibilities carefully – AIs cannot be held responsible for their behaviour!

Some practical steps organisations can take:

  • Meta-decision-making to ensure AI systems act in line with organisational ethical values.
  • Make sure third party algorithms adhere to ethical standards.
  • Establish a multi-disciplinary Ethics Research Unit.
  • Introduce ‘ethics tests’ for AI machines, where they are presented with an ethical dilemma.
  • Ensure staff have access to relevant training courses and communications re: ethical use of AI

What I will aim to do differently as a result:

In future I will:

  • Think about ethical and legal and other risks of AI projects at the design stage
  • Continue my learning and investigation of AI as applied to my organisation’s business
  • Consider whether ethics, compliance and legal teams should be engaged in AI projects.

Attitudes of the British Public to Business Ethics 2017

What it was:

Review of an article on business ethics current trends as part of my CIPR CPD. Source: https://www.ibe.org.uk/userassets/briefings/ibe_survey_attitudes_of_the_british_public_to_business_ethics_2017.pdf

What I learned:

Trust in business ethics has recovered very slightly (48% to 52%) since last year

The key issues of concern are:

  • Corporate tax avoidance
  • Executive pay
  • Exploitative labour practices
  • Work/life balance

As an observation – these top 4 issues are (arguably) linked, focusing around perceived unfairness between senior executives and staff.

The report notes that the relative recovery in attitudes to business ethics could be driven by falls in attitudes to ethics in other sectors (presumably Government)

Among the lower-level issues of ethical concern, Human Rights has dropped off as a concern. Meanwhile Data/Privacy has grown as an issue of concern.

Millennials appear less concerned about data privacy, perhaps counter-intuitively?

What I will aim to do differently as a result:

  • Recognise that corporate reputation concerns are affected by current events and press coverage, just as in the public sector
  • Appreciate that the public’s issues of ethical concern evolve over time but show reasonable consistency from year to year – i.e. they are not overly driven by current events
  • Recognise that underlying themes (e.g. perceived unfairness between senior executives and staff) can manifest across numerous ethical themes
  • Remember that different generations of staff may react differently to ethical issues.

CIPR Webinar – Change Communication

What it was:

CIPR Webinar on Change Communication presented by Alison Arnot.

Source: http://bit.ly/1El4UJS

What I learned:

Overall points from the webinar:

  • Change is a normal part of business process so a successful business must be able to do it sustainably and repeatedly.
  • People naturally wary of change. It is experienced differently by different people
  • The change curve is superficially similar to the grief curve!
  • Communicators job is to help people move through the change process
  • Those closely involved in the change process typically have a different view as they have more insight and empowerment in respect of the change.
  • Ultimate goal is to get people engaged and motivated to help deliver the future
  • Measurement / evaluation is key. You can’t influence what you don’t understand
  • Measure effectiveness, understanding, feelings, engagement and behaviour
  • Can use e.g. Bench-marking and demonstration of objective evidence of actual changes in behaviour

Detailed points:

Change communication strategy needs to include…

  • Why communicate? Who communicates with whom and about what?
  • What channels? When?
  • AND Consequences and measurement?

Analysing stakeholders needs to ask…

  • What is it like working with us? Who influences them? Who do they influence
  • What is our place in their aspirations? What is their view of our future? How can we help each other?
  • What is their motivation/agenda?

Stakeholder mapping – “Power vs. Interest”

  • High power low interest: Keep satisfied – A threat if they don’t understand
  • High power high interest: Engage – Can make or break your programme
  • Low power low interest: Monitor – Inform but don’t overload
  • Low power high interest: Inform – An advocate and ear to the ground

Communication content needs to address….

  1. STRATEGIC Information
  • Vision, values and direction
  • Rationale and benefits of the change
  • Comms outcome: Sense of purpose
  1. CORPORATE Information
  • How we are progressing?
  • Is the change helping?
  • What success is being had?
  • Comms outcome:  Sense of progress
  1. OPERATIONAL Information
  • What we need to start, stop and continue doing to make the change a success
  • Comms outcome: Sense of control

Messaging needs to address the three following needs…

  • Personal needs – a realistic (not evangelical) appraisal of the situation and what it means for me
  • Operational needs – where we are, where we need to be, what we need to do
  • Strategic needs – the big picture

What I will aim to do differently as a result:

I will conduct a stakeholder mapping exercise (identifying them all, then mapping power vs interest) for my digital transformation programme.

I’ll tailor our programme comms to ensure it covers the Strategic / Corporate / Operational content-types outlined in this briefing.

I’ll ensure that our messaging is better at addressing the three “needs” i.e. Personal / Operational / Strategic.

I will design a system of bench-marking for the programme – potentially a maturity model. For example %age of people that agree with each of the 10 statements in the digital vision.

Civil Service Alumni: Introduction to Artificial Intelligence

What it was:

Talks by subject matter experts on AI hosted by the Civil Service Alumni, at the Royal College of Defence Studies, London on 18 December 2017

What I learned:

AI is permeating business:

  • No single agreed definition of “AI”
  • ‘Narrow’ AI does specific tasks, as opposed to ‘General’ AI which can solve new problems
  • AI is already in use in hundreds of Google products
  • AI is increasingly in the plans of the forward-looking global industrials
  • Huge landscape of firms involved in different sectors

Deep Neural Networks:

  • The workhorse of modern AI is the deep neural network, where each layer of neurons is connected to the prior layer
  • Supervised versus unsupervised learning
  • AI performance is better than humans in many narrow case, using supervised data and deep neural networks

Conditions for success:

  • Many AI applications can be characterised and understood as input X leading to output Y to solve problem Z.  For example, medical scan data leading to disease symptom recognition to solve diagnosis.
  • A precondition for the successful deployment of AI is a clear definition of the system or process, and an understanding of what AI can do
  • A social technical approach, including human impact, is typically desirable
  • AI typically requires widespread digitisation of the system
  • Data requirements: Common definitions, high quality, accessible, sufficient size
  • Domain expertise is key

Impact on Government?

  • A viable, shared business model for both public and private sector is needed
  • Key challenges for government in terms of  capability, ethics, regulation, getting on front foot in terms of impact, and in nurturing the wider AI economy
  • There is a significant discussion happening now around ethics, bias, regulation

What I will aim to do differently as a result:

  • Think about ethics and regulation of AI
  • Think about impact of AI on Government, including potential oportunities
  • Continue my learning theme on AI!

Strength Deployment Inventory (SDI)

What it was:

An exercise to measure ourselves against the Strength Deployment Inventory (SDI) model (aka ‘red green blue triangle’) as part of the Future Leaders Scheme at Ashridge in November 2017.

What I learned:

I came out of the SDI exercise as red (“asserting / directing”) but close to red-green (judicious / competing) and the hub (flexible / cohering). Under stress or pressure I move to the hub.

I recognised all three in me, but perhaps the hub most of all

Your self-perception is based on your motivation, which form as intentions, which in turn express as behaviours.

Other people’s perceptions of you are the other way round – they are based on your behaviour, which expresses your intentions, driven by your inner motivation (which other people can’t see!)

What I will aim to do differently as a result:

  • Learn more about what I can do with SDI
  • Recognise when people are moving along their long vectors, it should be obvious they are stressed.
  • Note that for people with short vectors, it may not be obvious they are stressed, I may need to come to them to see if they need support
  • Always maintain healthy scepticism of SDI and similar personality models!