AI – is it ‘Artificial intelligence’ or ‘Augmented Intelligence’? Is there a difference?
Well, one must give due credit to Hollywood for making AI a popular and fascinating concept for the masses. In 1927, we saw the first movie with hints of AI – Metropolis, where a robot named Maria was created with the likeness of a human, and a mind of her own. Unsurprisingly, she went on to reign terror – leading to massive destruction, until a human rectified everything by acting as a mediator.
In other words, we can blame Hollywood for showcasing AI as evil, or, maybe, prophesying the evil side of AI, which looks unlikely in real life.
Switching to factual research from movies, Gartner relies on solid data to predict that AI Augmentation (which is Augmented Artificial Intelligence and not your usual Artificial Intelligence – more on that later) will create US$2.9 trillion worth of business value and 6.2 billion hours of worker productivity globally by the year 2021. That certainly is massive!
But what’s the difference between the AI (Artificial Intelligence) of Hollywood and the AI (Augmented Intelligence) of reality?
In straightforward terms, Artificial Intelligence refers to the science and engineering of making intelligent machines. Artificial Intelligence works by combining massive amounts of data with smart algorithms, which allows the software to identify and learn from patterns in the data, and replicate them.
‘Augmented Intelligence’ also refers to the same thing – but the term ‘Augmented’ emphasizes the fact that ‘Artificial Intelligence’ is a set of technologies meant to help humans, and by augmenting various processes (not replacing them), they lead to the catastrophic events predicted by some top-grossing movies in Hollywood.
Industry 4.0 and AI
The latest revolution of Industry 4.0 would be heavily automated and dependent on intelligent machines. These smart machines, powered by machine learning, are nothing but extensions of AI, which has been hailed as the key driver of growth across industry sectors.
However, the common assumption that AI will replace humans is not correct. While AI is expected to drive our cars (think Tesla) and automate our work (think COIN by JP Morgan Chase) – these time-saving innovations cannot override human innovation. That being said – AI can effect massive savings for various industries – like Chase’s COIN, which uses machine learning to review complicated documents, taking only a few seconds to finish regular tasks that previously took up to 360,000 hours to complete!
On Becoming an AI-Fueled Organization
Gartner, in one of its reports, points out that the growth in ‘Augmented Intelligence’ is mainly driven by the need to improve customer experience. By relying on intelligent technology, companies can boost customer convenience, introducing a high degree of personalization, and also reduce human error, which can lead to cost savings.
Thomas H. Davenport, in his book “The AI Advantage,’’ shares the three stages that an organization may follow to unlock the power of ‘‘Artificial Intelligence.
The first stage- Assisted Intelligence has already been achieved by most companies or is currently being tested. It is implemented by autonomous vehicle companies for driving safety systems, controlling speed, and activating the brakes if necessary.
The second stage- Augmented Intelligence, where machine learning capabilities are integrated into existing systems to augment human analytical competencies, is critical in the process of AI adoption. Netflix is an excellent example to understand this stage. Say, a user recently watched the series ‘Narcos’ on Netflix. Netflix may now suggest other shows or movies with similar themes – series based on true events related to crime. Based on your actions, Netflix’s recommendation engine predicts what you’d like to watch next. And, based on your subsequent selections, it continues to customize your experience.
In the field of healthcare, Tampa General Hospital has launched a command center powered by over 20 AI-based apps to determine the availability of beds, track the progress of the patient, expedite tests and test results, and also predict any likely delays in the care-giving process.
The third stage or the stage of Autonomous Intelligence will see a higher degree of automation where machines can directly act upon the intelligence derived by them. There are several examples of this stage, currently being experimented upon in the transportation industry. Key examples are self-driving cars and ‘Advanced Driver Assistance Systems (ADAS)’ that take multiple inputs from external devices like cameras and sensors, and internal inputs from braking, steering, and accelerator position to significantly improve the speed and response of the driver to rapidly shifting conditions.
Zensar can assist you to Make the Switch
The journey from Assisted Intelligence to Augmented Intelligence and further on to Automated Intelligence must start with the identification of the critical areas and making sure the adoption aligns to business goals and is backed by a clear strategy, Once these areas are identified, the next step is exploring various potential use cases and measuring the results in terms of specific and consistent metrics – which is crucial in measuring the success of ‘Augmented ”Intelligence’ solutions.
Zensar has a proprietary AI/ML and Big Data Platform, ZenAnalytica, which is a suite of solutions & accelerators across data to insights journey to meet all data-centric needs of an enterprise. With a pick-and-choose model, customers have the flexibility to choose individual solutions/accelerators or the entire platform depending on their business needs.
In addition to this, our Augmented Analytics platform (powered with AI) is specially designed for business users and citizen data scientists to assist them with exploratory data analysis and on-the-fly insights generation helping in quick business decisions. ZenConvo, our ML and NLP based conversational analytics platform, gives enterprises an enhanced digital experience in uncovering insights from their data.