Neuroscience’s recent advances have made way for innovative applications that cognitively augment and enhance humans in different contexts. Human enhancement belongs to a broad range of techniques and approaches to the increasing body or cognitive functions through medical implants, performance-enhancing drugs, prosthetics, human-computer teaming, etc. The results include enhanced characteristics and capabilities that sometimes go beyond the prevailing human range.
The History and Future of Cognitive Augmentation
Over the last two decades, the term human enhancement has been discussed in great detail. Scientists are defining whether an intervention that only restores function lost due to injury, illness, or disability is still an enhancement. Cognitive enhancement can be best defined as improving processes of acquiring or generating knowledge and comprehending the world we live in. These processes include the following:
• Attention seeking factors;
• The formation of knowledge;
• Memory-related aspects;
• Judgement and evaluation;
• Reasoning and computation;
• Problem-solving and decision making aspects;
• The comprehension and production of language, et al.
Thanks to the development of techniques that can record and stimulate neural activity, we can better understand the cognitive mechanisms in the current context in the tied to perception, attention, memory, and the planning and execution of actions. However, we can only know how practically all these techniques can be used for cognitive augmentation, depending on how effective they are at detecting interpretable neural activity and stimulating specific target areas of the brain.
But most importantly, what is the degree of invasiveness that remains a pivotal question? To what degree does the technology need an introduction of instruments into the human body? How expensive and how portable is the technology that should matter the most? All these questions influence the practicality if using such technology for human cognitive augmentation.
What is Neuroergonomics?
Neuroergonomics focuses on the neural and cognitive mechanisms that support human performance in the workplace and everyday tasks. It uses this knowledge to develop systems that help humans perform all these activities more safely and efficiently. BCIs are connected to providing people with severe motor disabilities a way to replace or compensate for lost functionality. For example, BCIs can help them control computer cursors or wheelchairs or communicate differently if natural methods are not possible.
Advances in neuroscience allow us to gain an in-depth understanding of neural processes. The most recent advances have opened our eyes to how people approach decision-making, strategies they use and their aptitude for risk-taking behaviour. There has been a focus on the BCIs in the contexts of decision-making, face recognition, target detection, and localization. The development of collaborative BCIs has led to newer applications such as robots, video games, cursors and simulated space crafts. It also entails spellers, analyzing people’s neural signals while watching movies and identifying a relationship between the shot’s length and the amplitude of large-scale ERPs. We now have neuro-stimulation techniques, like ES and TMS, which can help to improve human performance in various cognitive domains, such as:
• Learning and memory;
• Decision making.
This promising field has spurred more research into technologies that monitor cognitive performance and capacity.
Intelligence Amplification(IA) vs Artificial Intelligence (IA)
We can trace Intelligence Amplification (IA), cognitive augmentation, or machine augmented Intelligence to the 1950s and 1960s. Cybernetics and early computer pioneers raised this concept. Intelligent Amplification or IA refers to the effective use of Information Technology (IT) for increasing human Intelligence.
Furthermore, IA is often compared with AI or Artificial Intelligence. AI is developed to make a computer ‘smart’. It involves making a computer with human-like intelligence to perform autonomous workflows. For AI to succeed, it requires much better models and data. IA can fill that lacuna. IA has existed for many years, but it hasn’t been widely recognized.
However, we now have systems like HoloLens, which can help IA be the faster element of AI. Indeed, IA has the potential to offer safer methods of developing tools and technologies that acquire efficacy from human consciousness instead of building their Intelligence. IA-developed tools can be utilized for many purposes, such as those mentioned below:
• Natural language tools;
• Developing knowledge bases;
• Electronic discovery;
• Image processing tools.
The Future of Intelligence Amplification
Intelligence Augmentation (IA) relies on Machine Learning technologies. These are similar to Artificial Intelligence (AI), but IA aims to assist them rather than replace humans. So, instead of entirely relying on a machine for business processes, IA Machine Learning works in conjunction with the human brain. IA aims to make a more efficient and certainly a highly productive workplace. However, unlike AI, it seeks to do so in tandem with humans to support discoveries and problem-solving. AI, on contrary wishes to do the same, but it bypasses humans altogether.
For example, let’s take a Machine Learning algorithm that processes enormous amounts of patient data by going through patient history, previous records, family history, data from wearables, and tests to predict illness. This information will be given to a medical staff that supports a doctor. This doctor would use their reasoning to offer a diagnosis. It is considered Intelligence Amplification because a doctor (human element) is involved in the whole process. However, if the program was only meant to sort the data and diagnose, it would be an Artificial Intelligence framework.
IA technology could be well-utilized for complicated medical procedures, as there is much scope for improvement in it. All over the world, researchers are developing tools for the same. Researchers in Cambridge have discovered potential solutions by combining MRI and CT to create 3D images of a patients’ bodies. It will help the surgeons perform more accurate surgical processes.
To conclude, there is no competition between the technologies of IA and AI. They are both essential technologies that can benefit us in our day-to-day lives and processes. As the technology keeps advancing every day, IA can be utilized to address the various challenges related to AI. We must find new ways of making the two technologies work together. Such efforts will contribute significantly towards the betterment of society as a whole.