How are Assisted Intelligence and Augmented Intelligence Different?

by July 29, 2020 0 comments

AI

Understanding the difference Between Assisted Intelligence and Augmented Intelligence and how they are useful

Artificial Intelligence (AI) has been a transformative force over the past few decades driving innovations and leading us towards a better tomorrow by mirroring human intelligence. But now, there are two other recurring and advanced version technologies which hold a better chance to supplement the digital transformation we have been observing taking place. These are assisted intelligence and augmented intelligence. Both of them hold potential answers to the age-old questions like: ‘Will artificial intelligence be able to work alongside with human intelligence?’, ‘Can it enhance our performance capabilities?’ ‘How much power it can have and when should humans intervene?’ and others. In this article, we will help you to understand the basics between assisted and augmented intelligence, where they differ and why both are necessary.

 

Assisted Intelligence

It is often considered as a basic form of Artificial Intelligence and is mainly used to automate simple tasks and processes. This is achieved by harnessing the combined power of  Big Data, cloud and data science and is least suited in decision-making. Though it requires constant input from human users, it frees people up to perform more in-depth activities with clear outputs. The main objective is to improve the processes that are already taking place, i.e. it alerts humans about possible solutions and allows them the authority to make final decisions. Some of its immediate applications are in transportation, healthcare, and as a personal assistant—E.g. GPS navigation programs used by drivers.

 

Augmented Intelligence

It aids human intelligence and enables people and organizations to do things they cannot do otherwise, in faster and smarter ways. It is based on machine learning, natural language processing, image recognition, and neural networks. The prime role is to support human decisions rather than simulate independent intelligence. It abides by a five-function cadence that empowers it to learn with human influence. This sequential process comprises of

1. Understanding the system data input,

2. Interpret new dataset based on old data learning analytics,

3. Creating output of the new data via reasoning,

4. Learning from the human feedback on its output through comparative analysis and readjusting itself accordingly and finally,

5. Assuring security and compliance based on AI and Blockchain algorithms.

Some of its immediate uses are in finance, cybersecurity, healthcare, public safety, fraud detection and many more spheres. E.g. Risk analytics and regulation tasks carried out in banks.

 

Where to draw a line of demarcation?

It is essential to understand that both these technologies democratize productivity gains. However, their application depends on the requirements of industries. For instance, assisted intelligence is leveraged in customer engagement sector in retail, whereas, A/B testing in e-commerce decisions. Similarly, in healthcare, while assistance is provided in the form of chatbots to patients, at the provider end, there is ‘augmentation’ in the form of diagnosis.

Sometimes they complement each other too. The GPS navigation system which ‘assists’ people to arrive at their desired location hassle-free, also led to the birth of UBER, where anyone with a car can be a driver. The latter is where same GPS technology augmented the capability of a user. This is why augmented intelligence is considered to expand the employment pool by reducing the skills needed to complete a task. Moreover, it provides humans with a more controlled and operable environment. Hence, companies prefer to start with augmented intelligence approaches since it presents the most immediate opportunities for ROI.

So, what business leaders need is to examine what are their goals and identify with versions of AI will help them gain higher ROI and further the cause and productivity, or if they can employ both assisted and augmented intelligence. Then they can analyze what they want their employees to continue working on and how they shall share control over tasks when employing these technologies.

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