Sunday, July 12, 2015

The Path Towards Automated PR

Public Relations is a profession, an art and is safe from automation, some might say. In my forthcoming book, we will see that such ideas are outdated. The machines are far too clever to be left out!


The biggest benefit of automation is that it saves labour and increases productivity. It is also used to save energy and materials and to improve quality, accuracy and precision.


It also replaces the jobs of many. In the past, this has been to the disadvantage of the inadequately educated and lackluster folk in society. No more. New developments will be a challenge to all but the most creative and capable in society.


Many people believe that automation requires human buy-in to succeed. Evidence in this book will suggest that it will often be hard to identify the application of automation in the first place. It is sneaking up on us. Buy-in will be more cultural than emotional or pragmatic.


It has to be said that all PR will NOT be automated.


Many facets and processes of PR will be fully, or partly automated. Some activities will be transferred from human delivery to the processes offered by new and evolving technologies.The profession will be changed by automation and these evolving technologies replacing PR functions, and wider environments will alter the nature of PR.


For those who hang their hat on the uniquely creative nature of PR, there will be a disappointment. They will discover that, progressively, technologies are beginning to automate many of the most creative of aspects of modern civilisation. PR will not be exempt.


The key here is whether, as in the past, external actors provide the products, services, code and Apps. The alternative is for the PR industry takes it unto itself to get involved and encourage relevant design capabilities to address the issues it faces in automating and changing the productivity of the sector.


In this book, we begin with an examination of automation and then look at the ordinary and mundane. We have to look at current capabilities such as such as automating SEO and progress to more advanced forms of activity that will replace many of the humans who work for the PR sector. After that, there is a little blue sky commentary.


An example of ordinary and elementary PR might be an activity — let’s say a new post on your blog. The first step in automation will be that it triggers an action, such as sharing that post on Twitter and Facebook. It’s a simple process. Thus, an event happens in one environment, triggering an event in another place. Such ability can be incredibly powerful when you use it to tie together over 350 apps in this way, which is a service already provided by Zapier (among many others).


The big question for the PR sector is whether developing such capability should be part of PR sector development or third party initiative. In other words, is it possible for the PR industy to create a supporting development infrastructure for practitioners and vendors.


While this might be a PR sector activity, other actors are doing the same sort of thing from their perspective.


For example:


Google’s new ‘Knowledge Graph’ allows Google to move toward a new way of searching not for pages that match query terms but for “entities” or concepts that the words describe.


In March 2015, the President of the Chartered Institute of Public Relations discovered that a robot had created a biographical note about her, including a photograph and noting her election to Institute President.  It appeared for all to see in the right-hand column of Google Search. The robot had already visited the PR profession and automatically written up a nice little column. Almost no one noticed, not even Sarah Pinch until it was pointed out to her.


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Thus, many PR activities will be modified or usurped by new services or by organisations that have more power and capability than the PR industry can summon up to offer an alternative..


In such circumstances, the profession has to be aware of these many changes;  has to monitor what it is doing and has to be able to manage the events that are beyond the control of the PR sector. The PR industry now has to develop capabilities to identify new technologies that are relevant for the profession and has to ensure its members are fully aware and capable of both recognising such techniques and able to deploy them (whether they like it or not).


Automation goes further. It is affecting the actors that are influencing PR constituencies.


Four in five (82%) people are accessing online news in the UK, access the website or app of a traditional news brand. Of those who access news on their smartphone, half use a single source on their phone. In other words, web technologies collect, collate, re-format and publish news without a single human touching it but from established news brands. Is this automated content distribution legitimate or even ethical? Can it be a revenue source for publishers? How should the PR profession optimise this development?


Despite the benefits of such super technologies, funding them is hard work, Reuters’ did the research and found that the digital audience will not pay. Three-quarters (73%) of UK adults say they are very unlikely to pay for online news.


This is a behavioural change.


Perhaps news distribution will be saved by online advertising.


PageFair reports research with Adobe showing that in 2014 there were about 144 million active adblock users around the world and adblock usage grew by nearly 70% between June 2013 – June 2014. Wark.com reported that only half (52%) want to block all ads, according to more than 2,000 UK adults questioned by YouGov for the Internet Advertising Bureau UK. There is more to this area of development. But the essential truth is that news publishing is being changed by automation. Today, news content of the ‘broadsheets’ has to fit mobile phones and the advertising model is also changed after centuries of success.


For Public Relations, this is evidence of third party change in the PR business environment wrought by the internet and automation in other sectors. The profession needs to know of such changes, the potential effects on practice and a view of what is happening next.


So far, the changes we are experiencing are what we, mostly, see every day. There are activities that are less evident, can affect or be adopted by practitioners and point to a very different future.


We are talking about big, complicated, subtle cognitive tasks which are quickly being affected by digital agents. Some are evident in very practical applications like wikis, others are even more advanced and that’s a sign of things to come.


This is here where the PR industry has to look.


Is there software that can rationalise and describe the product manager's’ monthly statistical analysis? Can it be re-cast into a well written commentary? Can this be re-framed and offered to a wider range of interest groups in the cultural sphere of the organisation?


Take a deep breath. The answer is yes! Better still, it is an automated capability. Can it be re-formatted to serve wider and new audiences in near real time or selected times? Yes it can.


Now we are entering the domain of technologies able to usurp a number of the traditional activities of the PR sector.


This is the area where, for example, some press releases/notices can be created automatically. They can add to the transparency of organisation in addition to removing some of the more tedious work.


A minor earthquake in Los Angeles early morning in March 2014 was relatively unremarkable apart from one thing: the first news report of the event was written by a robot.


The Los Angeles Times was the first media outlet to publish news of the earthquake, putting up a news report on its site only three minutes after the first tremors were felt. The story appeared under the byline of Ken Schwencke, a journalist and programmer at the LA Times.


But the real author was an algorithm known as Quakebot.


The report said:
“A shallow magnitude 4.7 earthquake was reported Monday morning five miles from Westwood, California, according to the U.S. Geological Survey. The temblor occurred at 6:25 a.m. Pacific time at a depth of 5.0 miles.
According to the USGS, the epicenter was six miles from Beverly Hills, California, seven miles from Universal City, California, seven miles from Santa Monica, California and 348 miles from Sacramento, California. In the past ten days, there have been no earthquakes magnitude 3.0 and greater centered nearby.
This information comes from the USGS Earthquake Notification Service and this post was created by an algorithm written by the author.”


Everyone agrees, this is not the greatest prose ever written but the computers are still learning.


Minutes after Apple released its record-breaking quarterly earnings in January 2014, the Associated Press published (by way of CNBC, Yahoo, and others): "Apple tops Street 1Q forecasts." It is the headline followed by a 200 word financial story written and published by an automated system well-versed in the AP Style Guide. The Yahoo post scripts says “This story was generated by Automated Insights (http://automatedinsights.com/ap) using data from Zacks Investment Research. Access a Zacks stock report on AAPL at http://www.zacks.com/ap/AAPL”


This AP implemented system now publishes 3,000 such stories every quarter — and that number is poised to grow.


Quarterly earnings are a necessity for business reporting — and it can be both monotonous and stressful, demanding a combination of accuracy and speed. That's one of the reasons why last summer the AP partnered with Automated Insights to begin automating quarterly earnings reports using their Wordsmith platform.


According to Automated Insights  public relations manager, James Kotecki, the Wordsmith platform generates millions of articles per week; other partners include Allstate, Comcast, and Yahoo, whose fantasy football reports are automated. Kotecki estimates the company's system can produce 2,000 articles per second if need be.


To get some idea of the range of organisations being reported by this system, a news search for "This story was generated by Automated Insights" will show how pervasive this form of media relations has already come (over 30,000 reports at time of going to print).


This is now getting close to some day-to-day media relations PR work. It is not very sophisticated and is based on an algorithm and application of semantics. It offers a potential revolution for much work in a Financial PR division of a big company.


Perhaps it is time to introduce ‘Deep Mind’.


DeepMind co founder Mustafa Suleyman gave a rare insight into the work he and his team are doing within Google during a machine learning conference in London in 2015. He leads research at the company.


Google DeepMind is an artificial intelligence division within Google that was created after Google bought Oxford University spinout, DeepMind, in January 2014.


The division, which employs around 140 researchers at its lab in a new building at Kings Cross, London, is on a mission to solve general intelligence and make machines capable of learning things for themselves.


Suleyman explains:


'These are systems that learn automatically. They’re not pre-programmed, they’re not handcrafted features. We try to provide a large-a-set of raw information to our algorithms as possible so that the systems themselves can learn the very best representations in order to use those for action or classification or predictions.'


'The systems we design are inherently general. This means that the very same system should be able to operate across a wide range of tasks.'


'AI has largely been about pre-programming tools for specific tasks: in these kinds of systems, the intelligence of the system lies mostly in the smart human who programmed all of the intelligence into the smart system and subsequently these are of course rigid and brittle and don’t really handle novelty very well or adapt to new settings and our fundamentally very limited as a result.'


'We characterise AGI as systems and tools which are flexible and adaptive and that learn.'  


‘We use the reinforcement learning architecture which is largely a design approach to characterise the way we develop our systems. This begins with an agent which has a goal or policy that governs the way it interacts with some environment. This environment could be a small physics domain, it could be a trading environment, it could be a real world robotics environment or it could be a Aatari environment.The agent says it wants to take actions in this environment and it gets feedback from the environment in the form of observations and it uses these observations to update its policy of behaviour or its model of the world.’


What he is explaining is common among humans. We are programmed to learn and we focus our learning based on a reward system at our mother’s breast.


In PR we did not really notice the application of Deep Mind. We are impressed with the capability of Google to find images from search instructions described in English in ‘Google Images’. It is just one example of the application of Deep Mind automation .


Automation is already at work in helping practitioners. What is not well established is the nature and benefit of these developments in day to day PR work.


Such developments have not been introduced especially for PR practice. It is right we know about such developments and use it and it is important that the PR industry can recognise the real thing and the scams.


In addition, there is a good case for the industry to seek out developments that will enhance practice (and increase productivity and competitive edge).


Furthermore the PR industry also need to be driving and rewarding useful development to aid practitioners.

These considerations are important for the PR sector and if it were to take them further could be a significant exemplar for the UK government trailed plans to publish a ‘Digital Transformation Plan’, in 2015,. It is an initiative which will set out the actions the government will take to support the adoption of digital technologies across the UK economy including, we hope, Public Relations.

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