Defence digital masterclass @ Barclays Rise

What it was:

The first Defence digital masterclass, with various speakers on digital themes, hosted at Barclays Rise, Shoreditch, on 4 May 2018

What I learned:

Artificial Intelligence:

  • The AlphaZero AI algorithm learns from blank slate, does not just replay earlier human learning
  • Human beings already have symbiotic relationships with dogs, possibly we can see future relationship with AI?
  • Key valuable skill at the moment is being able to analyse convolutional networks
  • Future AI will not be evil but may do terrible things purely in trying to help
  • The UK 4G network is expanding to 99% coverage
  • AI is difficult to define… Douglas Hofstadter ” AI is whatever hasn’t been done yet”
  • Loose definition of AI: systems able to perform tasks normally requiring human intelligence
  • General adversarial networks, train the forger and the tester at the same time. Can be used to optimise at scale and pace.
  • Neuromorphic computing: chips that mimic brain function by only firing the ” neurons” when relevant, enabling high computational power with low electrical power
  • The lower power consumption may be a clue, from a macro (physics) perspective, that the chip is using more brain-like processes. Current traditional AI architectures tend to use many orders of magnitude more power than a human brain.
  • ‘Centaur chess’ where humans are supported by machines. Have beaten the best humans and best machines. Implies that human-machine partnership and process may be key to military success?

Different scales / types of digital transformation in businesses:

  • Business model transformation,
  • Customer experience innovation
  • Operating model transformation

Thirty five percent of P&G products come from outside the company via its innovation approach
Many innovative large companies are sustained or accelerated through government contracts and investment; it’s not the case that innovation only comes from private investment
Military rituals are similar to agile rituals?  Could be a useful alignment.
DEFRA are using machine learning to read incoming documents, identify the name and address etc, and direct the document within department

What I will aim to do differently as a result:

  • Develop our model for digital transformation in defence, and to think about the technologies that underpin it
  • Think about business and process transformation as part of the model
  • Think about the working environment.
  • Make better connections outside MOD… we need to move to an ‘outside in’ approach

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.

DMSD Agile Foundation and Pracitioner

What it was

A week-long course with tests and certification in London, on Agile project management techniques. February 2017.

What I learned

This is a comprehensive introduction to the practices of project management as set out in the industry-standard DSDM (“dynamical systems development model”) framework – more commonly known as “agile”.

Born from bitter experience in the world of enterprise software development, “Agile” project management can be applied widely, but is most suited to scenarios where the final product is malleable and can be iterated, where requirements and estimates are fluid or unknown at the start, and where the project must respond quickly to business change.

These are scenarios where traditional PRINCE2 / “waterfall” project management approaches often fail.

Agile is broadly applicable to PR practice – in particular event planning, producing publications, web development, and evolving campaigns which respond dynamically to feedback and external change (e.g. social media campaigns)

The DSDM framework is complex and comprehensive and covers key roles, products etc but can be summarised into eight key principles:

1. Focus on the business need
2. Deliver on time
3. Collaborate
4. Never compromise quality
5. Build incrementally from firm foundations
6. Develop iteratively
7. Communicate continuously and clearly
8. Demonstrate control

Two key techniques in Agile are:
1. MoSCoW – this is a way of prioritising requirements into Must/Should/Could/Won’t so that the project focuses on delivering the “must” requirements, using the resource for delivering the others as contingency to guarantee that the “musts” – at minimum – are delivered. Thus agile projects, unlike other approaches, act to fix time, cost and quality but vary *feature set*
2. Timeboxing – this is a rigid discipline in which the project is divided into fixed time intervals of iterative delivery, with built in co-ordination, review, acceptance and retrospective sessions. Fixing the time frames of an agile project ensures that whatever is delivered is delivered on time, with no prospect of delay. Combined with MoSCoW this is a powerful tool for ensure projects deliver what the business needs, when it needs it.

What I will aim to do differently as a result:

I will seek to apply Agile methodology and techniques to my team’s working.

Social Media Beyond Borders

What it was:

Lecture on the international aspects of social media, organised by PRMoment.com at Ogilvy PR, Cabot Square. Date: 19 January 2011

What I learned:

Sites like SocialBakers.com can give simple stats on Facebook usage etc
We use different meanings of “friend” on different sites and in different contexts
Dunbar’s Number (approx 150) – a nominal estimate (perhaps not scientific) how of many friends you can sustain – perhaps has relevance to social networks.
Social Networks are interest-driven; social interaction must add value; narrower interests make tighter networks
Are social networks transnational? It depends who your friends are!
Facebook dominates, but different networks are popular in different countries.
PRs should seek to establish relationships with moderators/editors as you would with journalists.
The Chinese prefer to click not search.
Arguably Flickr is the most truly global social network.
China has  active “human flesh search engine” which sometimes tracks people down.

What I will aim to do differently as a result:

Consider the international dimension when designing social campaigns and when thinking about channel choices.

Digital Participation and Engagement

What it was:

Talk on current Digital Participation and Engagement at Government Communications Network (GCN), 19 October 2010.

What I learned:

Government Departments should make their data more attractive if they want to help get their messages across.
Engage people in finding out for themselves. Show don’t tell. “Interactify” the data if possible.
Interactive data visualisations are not about ‘telling’ but about the ‘learning journey’ your visitors will follow.
Make it about them – for example “Your CO2 footprint”, “Your spending review” etc.
Capture your visitors’ data (how they moved the sliders, etc.) – it is valuable in its own right.
Agencies can be used generate bespoke visualisations.
Don’t lose the opportunity to get data out there and use it to tell your story – or someone else will mine it to tell a different story.
We can use visualisations in internal as well as external policy development.
Be clear what is success – useful end ideas / leads? Or simply the number of comments?

What I will aim to do differently as a result:

Use visualisations and use data to tell the story more in future