Hybrid intelligence is a way to use AI and human intelligence jointly to create new solutions in real-time. It allows a human user to enhance their level of creativity and respond to circumstances more quickly.
Hybrids could also help humans make better decisions than they could with just one type of expertise. As a result, hybrid intelligence systems are more natural and realistic, allowing users to interact with their surroundings more freely.
The Hybrid Intelligence concept gained popularity with the advent of the Internet of Things (IoT), machine learning, and artificial intelligence.
Artificial Intelligence, in the simplest terms, is machines designed to learn, reason, and act like humans, enabling bots to perform high-level activities with minimal human intervention.
As per the Oxford dictionary, Hybrid Intelligence is the combination of two or more distinct forms of intelligence. In the context of business and technology, it’s the combination of artificial intelligence and human intelligence.
Artificial intelligence is narrow. It may be good at conducting specific, defined tasks that can be mathematically computed and reasoned but fail on many fronts, so AI implementation has been slow.
The future of AI includes a hybrid approach that fuses machine learning, neural networks and human expertise to create a flexible and responsive system.
Why is AI currently struggling?
According to the MIT Technology Review, AI has been a curse rather than a blessing. Computers can learn new skills, but humans have failed to impart the knowledge needed in novel situations.
AI has limited application because it is hard to create systems that can adapt to new situations and are good at inductive and deductive reasoning.
The main reason is that AI systems are data-driven and lack the fundamental knowledge and common sense that humans possess and apply.
Narrow AI lacks an understanding of the actual world and how to relate words to each other. It’s unable to grasp the bigger picture and can’t link information from various sources to solve a problem and make new connections.
Humans are good at generalizing, but most AI systems can only handle specific cases.
Why is Hybrid Intelligence Important?
Artificial intelligence is decades old, and we can see the fruits of the seeds planted decades ago. But the fact is, computers and software techniques are still not as intelligent as humans.
Hybrid intelligence is all about humans and machines working together, combining their strengths to achieve more.
It is a symbiotic relationship where bots provide muscle, and humans apply their creativity, knowledge, and experience to make decisions.
Both are essential for progress. The most significant advantage of hybrid intelligence is that it can accept and apply knowledge about an unfamiliar situation.
It can leverage unstructured data, which is difficult for machines to process, to make decisions. The Internet of Things is a great example.
Machines can monitor and collect data from sensors, but it is difficult for them to understand the significance of this data. With hybrid intelligence, you can use humans to understand the importance of this data and apply the knowledge to make decisions.
The future of Hybrid Intelligence:
As researchers and engineers refine the algorithms, they will increasingly enhance human ability and experience in decision-making. Thus, hybrid intelligence is the way forward.
Artificial intelligence will collect, organize, and interpret data. It will assist humans in making decisions and solving problems. The combination of humans and machines will allow us to tackle challenges and issues that are difficult to solve without the help of artificial intelligence.
The future of AI includes a hybrid approach that fuses machine learning, neural networks and human expertise to create a system that will be more flexible and responsive.
This approach enables efficient decision-making, planning, and problem-solving, even in the absence of data or when data is scarce. It will also use unstructured data, which machines have difficulty processing and interpreting.
How to Get Started with Hybrid AI?
We can start it by leveraging machine learning algorithms, unstructured data, and human expertise. The first step is to examine your data and identify the benefits of incorporating AI into your business.
#1- Strategy is key to leading:
There is no doubt Hybrid AI is a tool that will help you to achieve your business objectives. But need to consider the following questions before implementing.
Do you want to reduce operational costs or accelerate growth?
How does your hybrid AI strategy align with your business objectives.?
Think about how best to fit technology to solve the problem rather than vice versa.
#2- Get the data you need:
When developing AI solutions, businesses should consider the information they need from their systems to answer questions.
This information can come in two forms: structured or unstructured.
Structured data sort out by category; unstructured data is more free-form and can include images, audio recordings, etc.
Sophisticated AI projects also work with streaming data in real time, yielding current insights that are immediately actionable.
#3- Build the infrastructure and implement the tools:
Hybrid AI infrastructure allows you to use data in ways that can help you make better decisions.
Some types of AI require complicated systems, but others may be simple and allow you to extract value from the underlying data quickly and saves time and money.
#4- Develop relevant skills and talents:
As the technology behind artificial intelligence moves forward, the demand for people with skills and knowledge to work with will increase.
Hybrid AI will require experts in both the technology and human-computer interaction fields who can contribute to the development of systems.
Types of AI Included in the Hybrid Intelligence Ecosystem:
a) Adaptive AI:–
Adaptive artificial intelligence is the ability of a computer to change the way it operates based on what it observes.
It is a sharp contrast to the way computers operate now, which is to follow a set of instructions.
A computer having adaptive AI can change its activity based on new information.
Adaptive AI does not know all the answers ahead of time. Instead, it can change the way it operates to achieve a goal. While traditional computer programs follow instructions, adaptive AI can change functionality based on observation.
Adaptive AI can learn from experience.
b) Learning AI:-
Learning artificial intelligence is what enables computers to improve their performance based on data.
Learning AI does not have to be programmed to improve performance. Instead, it can improve its performance based on data.
c) General AI:-
General artificial intelligence is the creation of a computer system that exhibits human-like intelligence.
It is a hypothetical computer that can simulate human intelligence, such as natural language processing, knowledge representation and planning.
d) Narrow AI:-
Narrow AI is a type of AI that specializes in specific tasks, like playing chess or driving a car.
e) Parallel AI:-
Parallel artificial intelligence is a type of AI that uses multiple machines parallelly.
f) Specialized AI:-
Specialized artificial intelligence is a type of AI designed to solve specific problems.
g) Symbiotic AI:-
Symbiotic artificial intelligence is a type of AI that collaborates and shares knowledge with other types of AI.
h) Virtual AI:-
Virtual artificial intelligence is a type of AI that exists only in a digital environment, like a computer or mobile phone.
Benefits of Hybrid Intelligence:
HI will significantly improve customer experience, provide a more personalized service, and make the supply chain more efficient by yielding greater returns and profits.
Hybrid intelligence is the union of machine learning and human-guided decision-making that lets data drive decisions and humans be more creative.
Limitations of Hybrid Intelligence:
Hybrid Intelligence may lack the availability and competence of human resources.
Advanced AI systems may require a lot of maintenance, which could be challenging with a limited number of support engineers and service providers.
Humans may find it tough to communicate with AI systems that are different from what we have now.
The codes used by AI are based on mathematics and logic, while humans communicate using language, which is a more creative activity.
Will Hybrid Intelligence affect Jobs?
It is difficult to predict the number of employees who will lose their jobs in the next ten years. But it is not unreasonable to assume that the percentage of jobs that will change is 100 per cent.
Few jobs are immune to the change in the next decade, thanks to digitization and a hyper-connected society.
Machines will do what they are experts at, while humans will continue working in their field.
The Road Ahead:
Most industry experts would agree that hybrid intelligence is the future. The AI-human interface via virtual assistants and other platforms will be wide and varied, offering an array of consumer applications and a range of market opportunities.
Imagine hybrid intelligence becoming integral to the human brain, changing our sociological, psychological and biological makeup.
It will revolutionize how we see human life, living and raising children in the new digital age.
With hybrid intelligence, machines will be able to learn new tasks on their own. Humans need to program computers to learn specific tasks, but gadgets will be able to adapt to new environments and solve problems on their own.
Hybrid intelligence will make computers more creative, autonomous, and self-driven.
A hybrid AI ecosystem can also find the solution for climate change, health care, and other global issues.