Strategy in the age of ‘robotic content’

We live in a world of information abundance. The ability to create, produce, market and distribute content in almost any form has becoming very easy. So easy that a shocking amount of what we’re reading is created not by humans, but by computer algorithms – perhaps even this post ;).

In the most recent post on strategy4telcomediatech I highlighted the need to consider the role that ‘bots’ play particularly in automating conversational commerce – ‘sales and service’. In this post I take a look at the use of ‘bots’ or algorithmic content in digital media, how it is shaping our consumption habits, content creation and some of the capabilities required in both traditional and new media organisations.

What is robotic content?

Algorithms and natural language generators have been around for a while. However, recent developments in computing power and increased access to big data have meant that they are getting better and faster. The sheer volume and complexity of the big data we generate calls for artificial rather than human intelligence to derive meaning from it all.

Robotic content is content that is produced and distributed by artificial intelligence. Examples include Associated Press’s (AP)  Automated Insight’s Wordsmith platform or Narrative Science’s Quill platform which is used by Forbes publishing sites. According to reports, AP is creating more than 3,000 AI-led stories per quarter which includes everything from quarterly earnings updates to sports reports and weather. Robotic content however goes beyond news – there are booksedited videos and websites being produced by robots – rounding  out a good portion of the content we might view.

The other aspect to robotic content that is important to understand is how it (and other content forms) are being distributed and consumed.

Media consumption and robotic content

Many people have moved on from linear viewing of content (e.g. Broadcast TV shows, Print news/magazines)  into on-demand (e.g. SVOD, SMOD) and increasingly on mobile devices. The places we now go to for content (e.g. Netflix, Twitter, Facebook, YouTube etc.) are even a step further from ‘on demand’ – they are ‘algorithmic on demand’ and offer the ‘next thing’ to watch or read based on your profile, friends, likes and dislikes. These algorithms help to find content to keep consumers on their platforms longer.  This makes sense in a world where there is so much information available – but it has some consequences.

Last week there was a lot of press from a Gizmodo article about Facebook’s trending news feed. Facebook’s relationship with publishers continues to evolve. With more than a billion people on the platform and many using Facebook daily, Mark Zuckerberg wants Facebook Instant Articles to be the primary news experience for people to have. The controversy in the Gizmodo article was probably a little overstated (who reads the ‘trending news’ section of Facebook?) but it did highlight that Facebook (more than other platforms or publishers) is an extraordinarily powerful media gate-way and yes…algorithms aren’t neutral even if the ‘appearance’ of the platform is (ask yourself: ‘is Facebook conservative or liberal?’). Evidence of the power of the platform could be seen when earlier this year Facebook prioritised video in its feed which saw a drop in referrals to other media websites.

We are well on our way to a world where a lot of content is created by robot and served up to us based on an algorithm. So what does this mean for publishers and content creators?

AI-first content = AI-first capabilities

Publishing and content creation has been transformed in many ways already – machines and automation already play a large role in modern media. However, as with a ‘bot strategy’ in e-commerce, taking an AI-first approach to media signals the need for new publishing and content creation capabilities. To maintain relevance and economic viability, publishers and creators should look to augment their content creation process with robotic content (increasing productivity), create content that is searchable by algorithms, manage alliances with platforms (e.g. mobile, hardware platforms) or create unique algorithms that serve up compelling content in new ways for viewers and readers in the mobile eco-system.

An interesting example of a traditional digital media publisher going ‘AI-first’ is Quartz’s news app. Quartz is a news service (not unlike any other) but in March this year launched a mobile app for its content. The content in the app is served up like an mobile chat back and forth with a friend – a conversational style. This indicates a few things – its mobile, its a differentiated experience for the reader (aimed mostly at millennials), it is short snippets of content (probably robotic) and first and foremost it is learning what people like and don’t like – training an algorithm. It is possible that Quartz could run its whole service with a bot and algorithm it refines through the app.

Narrative Sciences co-founder believes 90 percent of news could be algorithmically generated by the mid-2020s. This is just an indication of the kind of change to take place in publishing and content creation. Out of the change though, I hope that content becomes more relevant, interesting and we begin to see new innovative forms created.


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