What if Facebook's scooping up of our personal data is doing us a huge favour?
How can that be? Let's imagine, and think, really big for a moment.
Humans as corporeal beings may be facing an extinction event. We are destroying our eco-system at an alarming rate, making large tracts of land uninhabitable. Sperm count has fallen in developed countries by 50% in four decades. If the rates of decline continue we'll be hitting 'The Handmaid's Tale' scenarios before we run out of Earth to live on.
There are those that argue (Life3.0) that far from dieing out, we may be about to evolve. That evolution would see us abandon our bodies and attain consciousness as digital beings.
To do so would free us from the challenges of keeping our bodies in a decent state - alive for example, and enable us to explore the universe, giving meaning to the vast tracts of it that currently have none (because there is no consciousness out there to experience it).
With me so far? Ok. So how does that mean Facebook is doing us a favour?
AI needs a lot of data to start learning and doing things humans do. It will need even more to recreate conscious versions of ourselves to live in infinity as zeros and ones.
What if this is Facebook, Google, Baidu, Yandex, Amazon's real mission - even if they don't realise it themselves? They are gathering and storing the data - to enable our evolution-as-upload as part of (rather than subject to) The Singularity.
Someone has to do it. If Facebook wants to make use of my data in the meantime to personalise an ad or two - I think that's a very reasonable exchange.
Thursday, March 29, 2018
Friday, March 23, 2018
The whole Facebook-Cambridge Analytica debacle can be read as a lot of wailing and gnashing of teeth from people who like to see the internet as a wild west awaiting their control. But there is an important lesson for anyone using data.
First - why the fuss? There are already plenty of laws and forthcoming rules to prevent the misuse of data.
The General Data Protection Regulation explicitly states that someone's data cannot be used or stored without their express permission, for example.
So, even if you were to grant a company permission to use your data, you can't grant permission to them to use your friends’ data. A company can't ask for that or use that. Even Facebook realised this was a share too far in 2014 and ended the practice (which had until then been employed by 'abusive apps').
However, the argument is that all that data has already been hoarded by the bad guys. But GDPR will make every item they hoard subject to compliance. So even in the case of old data (which loses its salience by the second in any event) the hoarder must make it easy for anyone to remove their consent and retrieve their data.
That's going to be a challenge for bad actors. And when the auditors come calling they will face fines for every single data point. And these are fines at the scale of 'put you out of business'.
The short term issue for Facebook and, therefore, for much of digital marketing and communications, is the breach of trust. This is based on the notion that we didn't understand the scale of what could be done with the posts and likes and comments we gave away in exchange for better connection with people and information that was useful or interesting to us.
Facebook could act on this, at least re the instance of Fake News. They could set their engineers to work creating an algorithm to automatically add links to fact-checking or cross-checking validated sites.
They could of course do the same for their adverts. Imagine the potential to cut through the lies...
However, these are only solutions if you have difficulty filtering truth from deceit. In reality we humans have a brilliantly well-developed ability to see through bull.
Large parts of our brains are dedicated to sorting the trustworthy from the cheats. (Martin Novak's Super Co-operators says this was essential to our ability to live in co-operative societies). Target me with all the propoganda you like, I won't be voting Nazi.
So we do have a responsibility in this as individuals. We choose what we are willing to believe, and we must ensure we apply our innate abilities to spot the fraudulent at all times.
And naturally - any business or organisation handling data must do so with care and with all due respect for the owner. It is this respect for the owner that points to the most critical learning.
If the digital industry takes one thing from Facebook's woes, it should be this:
Since the value of data rapidly decays, the relationship with the human behind the data is always going to be of far greater value than the data assets themselves.
Data is not the relationship. It is the output of a relationship. Get one.
Thursday, March 22, 2018
One thing the AI revolution is teaching us is that work (at least the bit left for humans) is less about repeating tasks and much more about striving for goals.
Yet job descriptions, which function as both recruitment rule book and measurement and guidance tool, have mostly remained proscriptive and remarkably static.
Most of us know job descriptions rapidly become unsatisfactory. Today it seems they become a poor fit with reality faster than ever. Perhaps it is time to formalise and recognise this.? Understanding what we do often helps us improve it.
So let's abandon the job description in favour of the Job Hypothesis (or at least pass it to the task-compiling world the bots better manage). The Job Hypothesis - a minimum viable job description - should be our start point. It should provide a framework to seek candidates within and to give new starters an initial steer.
The hypothesis should emerge from your initial insights; about the market, the needs of customers and trends emerging from impacting technologies.
Add an understanding of the organisation's Why and What and you can start to work out How the role in question should support these.
From these insights you can shape what the purpose of the role is; the roles it plays in supporting the organisation's Go To Market strategies (by audience); and - crucially - the responsibilities versus gathering more insight in all of the above.
These will help define what success will look like (ie in meeting requirements in x way or by y degree).
But this first draft must only be described as a hypothesis. Success is in further, continuous refinement - making the role flexible to live market and business need and to emerging trends. This places the focus on change and rewards and formalises constant learning about the market, customers, technology and other drivers - with the intended benefit of iterating roles towards greater market fit - now and in preparation for the future.
This will not be helpful to those who are only comfortable being told what to do, or who want to do the same old things days after day. But you probably aren't recruiting many of those. Bots have that covered.
Friday, March 02, 2018
|Image via http://cesran.org|
The problem with a vote - much like any decision - is that we can only commit to an intention. We do not vote for the consequences.
In the Brexit case (and, for the record, I remain, a remainer) the national vote was for the intention to leave. It cannot have been for the consequences. These - as with many of our decisions, contained a very great many unknowns which are only unearthed in the practice of folllowing your intent.
There are lessons for anyone trying to make decisions in conditions of ambiguity (by which I mean pretty much anyone in pretty much any live circumstance today under which the setting of clear and definable constraints are absent).
Dealing with ambiguity requires a much more agile approach - a willingness to respond to additional insight learned from your rapid prototyping and testing with those for whom the results really matter..
Even strategy work today is conducted in rapid iterative cycles - rather than the big bang of old. That's because even at the strategic level, elements are moving so fast that the only way to proceed is in rapid, insight-driven increments. Minimum Viable Strategy is tested for fit for purpose in measurable steps,sometimes pivoting towards what evidentially works rather than what the strategy document insists.
This insight-to-value approach is increasingly applied in industry. Decisions aren't of the one-time only variety. Decisions are made based on insights drawn from your last response. You move forward fast, but built on truths. This is how we are dealing with the rapid-shifting realities of a world that can change at the speed of digital (versus that of atoms).
And into this world we ask ourselves a one-time only, never-mind-the-consequences question when it comes Brexit?
It;'s clearly time for a new kind of democratic process - insight-led, rapid iterative democracy..