The Algorithmic world around us
Humans have worked relentlessly hard in pursuit of a custom-made world that can function as per their needs. Technology is at the cornerstone of all the advances humans have made in this quest.
High-end technologies like Artificial Intelligence, Internet of Things, Big Data, Deep Learning etc have become colloquially used words today, thanks to the value they are adding in the life of a common person.
For example, Amazon’s Alexa is an artificially intelligent personal assistant that can tell you the latest news or read out a recipe or set reminders for you. It feeds off machine learning algorithms that make it smart enough to have meaningful conversations with humans.
Alexa and many such smart machines prove that algorithms are the heart and soul of the brave new world around us.
The Expanse of Algorithms – Our Lives are Spun Around Them
An algorithm is a process or a set of rules, to be followed in problem-solving operations by a computing machine. It can perform calculations, data processing and automated reasoning tasks. While staying out of sight, algorithms keep the modern machines running.
They make them think and act, as codified by humans. For example, Alexa is a voice-based AI device that is more than just attitude. A small jukebox looking device hides a plethora of continuously evolving knowledge aided by machine learning algorithms.
Amazon’s AI experts are using big amounts of data to make it understand human language and also be a better speaker. Alexa’s machine learning algorithms learn from the speech modulations of the professional narrators.
They fine-tune the machine’s synthetic female voice to make it as good as a real human voice. This is one of the many examples of algorithms being used in the world all around us.
Algorithms hide the complexity of machines. They stow away the intellectual property and codes away from human eyes and only let us use the final product.
Facebook is a popular case in point. The algorithms on the Facebook website decide what users see in their timeline. It is interesting how users do not get to see all of their friends’ posts. It is the algorithms at work deciding what to show them.
Similarly, Google search results are unique for everyone.
The recommendations on Netflix or Prime video are also tailored as per unique viewing history. As a user, one does not even need to register these things, but they still are critical to how we live today.
This curated world is being driven by algorithms.
The Good and Bad of This World
Google knows when a user has been looking for a particular book and when they turn to the search engine, they display the relevant ads to them. Similarly, Facebook displays content on a user’s timeline as per his interests. This tailoring of results brings a better user experience on the table.
It makes the internet more useful and contextual to the user. The more the user spends time on the internet, the better his preferences are getting captured every send.
The crowdsourced data from different users, applied with appropriate machine learning algorithms, help every benefit by easier google searches (who goes beyond page 1 any more), relevant news on facebook and twitter, amazon suggesting what we may buy, expedia offering relevant trips, and youtube showing the videos we are likely to watch.
US and European capital markets witness over 90% of trading done by algos, on behalf of humans, leading to efficiency.
While there are a plenty of good use cases of this world, there is a downside too. There are always 2 sides of the coin. Is it not too good to be true for facebook to show us the “relevant” news in our feed.
Or is it prone to manipulating human minds? Recently held US elections put the bad part in the limelight by showing how Facebook can manipulate user’s exposure to content and try to influence their decision making.
Machine learning arguably evolves in any direction without any oversight from humans and can be very risky. Any fake news over the internet can control the minds exposed to it and spur them into a negative action.
And what happens when financial markets are driven by algorithms, and something fails. Flash crash happens leading to markets meltdown.
It is said that there is much bias in algorithms as well. Carnegie Mellon University’s research showed that Google’s online advertisement system was said to display higher paying jobs to more males than females.
It is feared that data-based decision making will negatively affect human individuality and identity as well.
Can we trust humans to apply some filtering, their own analysis, on top of the algos curated content that they see?
OR would they blindly believe in algos ability to make the right decision for them, without even realizing how that may impact them.
Evolution and The Way Forward
Algorithms define the machines and their processes today. They help devices get smarter and connect to both humans as well as each other effectively.
As smart machines will process more big data every second the world over, these algorithms will help machines and artificial intelligence processes become even smarter.
There are hypothetical theories in technology like the Singularity theory which states that in the future, the intelligence of machines will surpass the intelligence of humans.
Their cognitive capacity will outrun that of the humans. It will be triggered by the runaway technological growth spurring unthinkable changes to human civilization.
However, this is just a theory. Since times immemorial, humans have observed both the positive and negative impacts of any technology that has been embraced by them and the algorithm-based smart technology of today bears no exception to this rule.
Maybe regulating the use of algorithms, ensuring users understand what it means and how to take out the biases. There is no denying that algorithms are here to stay and will continue to affect our lives in more ways than we know of today.
Saying this, it is also relevant to be prudent while using the technology that simplifies our life. Maybe the next big opportunity for entrepreneurs is to bring the prudence into algorithms to manage their wider adoption diligently.
