Dangers of Algorithmic Sourcing

The increasing pervasiveness of algorithms in everyday life disturbs me.

At the behest of many friends, I finally joined the 500 Pixels community and have begun uploading some of my better photos there for licensing. It’s an awesome place filled with pro photographers competing for the highest scores on their photos.

Yet, scores are determined by the amount of likes, favs and comments you get over a short period of time.

For all intents and purposes, you have a homogenous community of primarily male photographers who are either very good enthusiasts or professionals voting on photos. What gets top ranked? The general popular stream is dominated by surreal landscapes and pics of almost nude models with the occasional wildlife pic thrown in for flavor.

500 Pixels Popular

If you want a top rank of 99 on 500 Pixels, bring epic photoshopped scenes and beautiful scantily clad women. These are amazed photos, and deserved their popular ranking. But you can look at the categories to dig deeper. Some of the lesser ranking photos strike me as a better representation of the many things you can do with a lens (and Photoshop).

Here’s the thing, I stopped posting anything I don’t think can get a peak rating of 80 or higher on 500 Pixels. I just won’t do it. Because I don’t shoot almost naked women for a variety of reasons starting with respecting my peers and wanting to stay married, I post landscapes. Since I shoot more than just landscapes, for that reason alone the site is limiting in its artistic and creative scope.

Algorithmic Determination

3410837914_767f9a331a_o
Image by aloalo.

Algorithms impact our news choices, too. And our clothing choices. And what we read. And the movies we like.

It seems like algorithms are everywhere. Here are just a few examples:

  • Huffington Post and Mashable sourcing their news based on rising social media memes.
  • Colors and types of shirt you are most likely to buy (based on past purchasing history).
  • Books you should buy on Amazon.
  • Movies and TV programs you are most likely to enjoy on Netflix.

Is this healthy?

It depends. If you like the same type of thing over and over again, then perhaps algorithmic determination is OK.

Afterall, if you participate on the same sites and buy from the same vendors, then your general behavior will match your peers. As such the algorithms are likely to be correct most of the time.

Consider that 60 people eat the same seven meals every week.

Yum, pizza.

Crazy People Like Orange

2522462056_a12690515e_o
Image by balotto.

Because I am crazy, five percent of the time I’d like to buy an orange shirt. Yup, it makes my skin look like shit, but I like orange.

Orange was my favorite color as a child. I had orange and green dinosaur wall paper, and one whole wall was painted exclusively orange. I still remember it fondly.

The algorithms don’t know that, but based on what they see online they have predetermined that I will buy black and red and maybe blue. I do like my black T-shirts, but I also like splashes of bright color. And 5% of the time that means I like orange.

What to do?

No Growth

Manny-Moe-Jack

Image via View from the Blue Ridge.

How do things become popular? Someone has to try them first, and then they tell friends. Soon early adopters flock to the product.

Perhaps it becomes popular within a niche community (More surreal interior architecture shots, please). Enough people in the community participate in other social networks, and not just online. Work, family and neighborhoods count, too. People tell their friends, and show them the the new thing they like.

Suddenly, it is safe to try something new. But maybe it won’t be new. Because an algorithm already saw that seven percent of your friends tried something, and it knows you buy items as an early adopter. The site sources you an ad telling you your friends Manny, Moe and Jack bought it already.

Boom! You react and plunk down your credit card.

What’s so daring about that? Where’s the growth?

Cool to be Weird

14537361442_9330f7d9f6_k

In a world where anything can be customized to a unique taste, niche stores are popping up all over the Internet to serve the terminally weird. Now it’s cool to be weird.

As database technology becomes cheaper and cheaper, niche stores will be able to serve a customer with algorithmic offerings. Even the daring will find themselves served with the predetermined.

And the algorithms will only get smarter.

How smarter more accessible algorithms impact the inevitable break from the norm remains to be seen. Perhaps that same percentage of the population will be able to resist precision marketing in this form. Or maybe we will all simply accept the endless stream of data driven sales pitches, some subtle, some obvious.

It’s a change that will happen whether we like it or not. The train has left the station.

What do you think?

Beating the Algorithm

5811067378_e207ee4cbf
Image by MUMA Monash

In the old days of “influencer relations” (you know way back when in 2009), PR professionals targeted the magic middle and top tier bloggers, which triggered larger blog coverage, and then more often than not traditional news media.

Since then digital media companies straddled the space occupied by both traditional journals and the top tier of bloggers. They use algorithms to detect hot news stories before they trend in the blogosphere, then break the news before traditional players and bloggers alike.

Specifically, Mashable, the Huffington Post, Forbes, Google and the others use algorithms listen to chatter on the social web. When hot trends bubble up they source the content provider, assign a reporter, or in the worst cases use narrative science — computer-based news writing — to break the story first.

This effectively takes power away from PR executives to affect the news cycle through traditional influencer outreach, and in turn, empowers the crowd to determine stories.

Some news outlets use the crowd to validate top stories, too. Validation is embodied by shares on social networks and comments.

For example, USA Today features stories on its web properties based on the posts that get shared the most. The old assignment editor loses weight in these scenarios.
Continue reading “Beating the Algorithm”

Marketing Automation Will Improve

The most common complaint about algorithms is their lack of intelligence, specifically their inability to generate results that match human interactions.

Image by anthillsocial
Image by anthillsocial

Producing off communication and awkward misses can actually hurt brands more than help them. Perhaps the most publicly algorithm gaffes have been via Facebook social ads, which over the years have served up many publicly noted gaffes. Then of course there is the confusion that automation creates about big date, which for many is just sloppy data.

So, yeah, automation has its issues, but it will improve.

Continue reading “Marketing Automation Will Improve”

The End of the Social PR Revolution

Soup Lines
Image by OakleyOriginals

In building the program for xPotomac (February 25th), I sought to address a sea change in media evolution. That change spells the end for the social PR revolution, a marketing movement embodied by brand-led conversations over the past seven years.

We are currently experiencing a throttling of branded, online grassroots power. Specifically, it’s becoming harder and harder for marketers to be seen with branded earned media and social updates.

This evolution is best evidenced by the increasing role of owned and paid content placement (as discussed, content marketing is the 21st century nice description of advertising), and social or native advertising.

Other signs evidence this change, too. Social search and stronger policing of black hat SEO by Google has put a premium on paid search again. Facebook’s use of Edgerank to force companies and individuals alike to pay for attention is another harbinger of this fate.

The rise of big data and the forthcoming wearable computing revolution — themes that run throughout xPotomac — will cause a further throttling of online grassroots pipes.

Continue reading “The End of the Social PR Revolution”