The presence of algorithms in our daily lives seems to have crept up on us until, without warning, it’s now everywhere.
You can’t go online without having content recommended to you or sometimes shoved in your face, based on what an algorithm thinks you’d be interested in. Whether you’re doing work-related research or shopping for a product, search engines dictate which items show up first on your results page.
Algorithms have an impact on individual lives, largely because businesses have decided to make use of their power. And that influence has become a highly contentious issue.
AI has the ability to make decisions that can curtail your career prospects or access to credit and insurance. It can sway your voting choices. Mismanaged data can compromise your privacy, foster bias, and create surveillance states.
But it’s not just the average person who’s at the mercy of algorithms. Increasingly, businesses are making use of big data and letting AI call the shots. Is that a good thing?
The key to future success
Industry leaders set the tone for others to follow, and they’re finding extraordinary success through harnessing algorithms. Even a non-tech giant like UPS can optimize its fleet operations by crunching big data.
As a company founded on indexing the web and pushing relevant content in response to search queries, algorithms are at the heart of Google’s success. Their model isn’t a formula that would work for any company, let alone one with nothing to do with SEO or the internet.
Yet every business needs to pay attention to Google’s algorithms. The slightest change can make a huge difference in your online visibility, which cascades into your leads and conversion numbers.
It’s why their announcement of a May 2021 overhaul has sent companies scrambling to adjust with the help of core web vitals optimization services.
The same thing goes for businesses that rely on social media platforms like Facebook or Instagram for their marketing.
If you aren’t using algorithms in business, rest assured others are doing so. AI allows them to tap insights and achieve efficiency beyond error-strewn human capabilities. It’s what will drive success in a future dominated by machine learning and data-driven decisions.
Pitfalls and limitations
One major objection to the influence of algorithms in our lives is the lack of transparency, referred to as a ‘black box.’ Startups that develop algorithms view them as proprietary material, and in a poorly regulated industry, they can get away with a considerable degree of secrecy.
That’s a problem for individuals and businesses as well. It’s a far more challenging enterprise when someone else defines the rules and changes some aspects of the competition.
Business leaders outside of the tech sector are rarely in a position to interpret the workings of an algorithm, let alone create one themselves. Consequently, even if you develop an in-house algorithm, it’s easy to overlook the possibility that it would turn out flawed.
AI is certainly capable of machine learning, even deep learning based on neural net pattern recognition. But every student has a teacher, and even machines rely on a certain level of human input.
That human influence means there’s always a chance for algorithms to inherit bias. This can lead to the same inefficiencies and missed business opportunities that machines supposedly avoid. And once that bias has been established, it’s costly and time-consuming to remove and retrain the AI.
The business case for expertise
Due to their power, the use of algorithms in business isn’t going anywhere. But that doesn’t mean every organization has to be at their mercy.
Research by Gartner has profiled companies that benefit from algorithms into two types. The first covers those that operate on a programmatic model, in which processing and monitoring big data is an inherent part of their operations. The second model is platform-based, in which users are given shared access to an interface where they can buy and sell products or share and store content.
In both of those models, the advantages of algorithms are immense and evident. But there are two other business models identified by Gartner in which the need for algorithms is minimal at best.
Subscription-based businesses like Spotify provide users with the same content and may use algorithms to create recommendations. But the music itself is still produced and curated by artists and industry experts.
The artisan model of business is even more intimately dependent on expertise. Now and in the future, customers of artisan businesses will always value personalization and authenticity over automation and data-driven decisions.
Even in a future dominated by AI, individuals can take steps to live with minimal influence from algorithms. Businesses, too, can choose to operate on a model that emphasizes human expertise, even as their competitors rush to jump on the data bandwagon.
