Artificial Intelligence with Human Engagement – a powerful combination for the digital but humane future

 Artificial Intelligence is creating waves as the world gets digitized, processes get automated in the face of rising global population, concerns about environment and managing resources and livelihoods across the world. World population has just crossed 8 billion and stands at 8.1 billion, looking to reach 10.3 billion by 2100. Many of the problems with that growth can be fixed with technology.

Technology has put the world in the palm of one’s hands. AI is a great innovation with amazing features and potential to really impact the world, positively. It can impact human lives and livelihoods, across manufacturing, medical sciences, construction, energy, environment and so much more. It’s a fantastic tool when used with conscience and intelligence; a dangerous weapon if not used properly.

BACKGROUND

AI or Artificial Intelligence has a long history, unknown to many who see this as a relatively modern phenomenon. The field of AI research was founded during a summer conference at Dartmouth College in the mid-1950s, where John McCarthy, computer, and cognitive scientist, coined the term “artificial intelligence. Marvin Minsky (Carnegie-Mellon University) defines AI as "the construction of computer programs that engage in tasks that are currently more satisfactorily performed by human beings because they require high-level mental processes such as: perceptual learning, memory organization and critical reasoning”. 

Why has AI taken off now?

Artificial Intelligence has started disrupting a wide variety of domains. There are a few reasons AI is taking off now.

·       Availability & Access to Data: Data is constantly being shared by users and applications in public and private domains. Previously, customers and businesses were skeptical about sharing data and often held onto the data for fear of leaking information. Now, data is being shared continuously, knowingly, and mostly, unknowingly e.g., location, your preferences, topics you are interested in, items you like to buy, and activities you are doing and interested in. And, all this data is available in a digital format, ripe for computers and machines to consume. Some of the information is available in textual or pictorial form and may need significant processing to extract actionable data.

·       Data storage: With the advent of new technology and cloud infrastructure, data storage has become cheap and capacity almost limitless. Huge sets of data are now stored and readily available in structured or unstructured form.

·       Computational ability: Processing power to gather, clean, analyze, and perform computation of the data has increased exponentially. Big data sets are processed, analyzed, trained, and inferred from easily, much quicker than earlier. Issues around consumption of data and processing them efficiently and quickly do exist and more research is being done.

·       Sophisticated algorithms: With decades of research, algorithms have become smarter and mature. Advancements in Data Sciences, Machine Learning, Heuristics, neural networks, and recently Quantum Computing, has made processing and derivation of results much faster and more relevant.

Artificial Intelligence – it’s wide range of uses

Artificial Intelligence (AI) has a wide range of applications across various fields. Here are ten of its top uses:

 

·       Healthcare: AI is used for medical image analysis, disease diagnosis, personalized treatment plans, drug discovery, and patient management, improving accuracy and efficiency in healthcare delivery.

·       Finance: AI is employed for algorithmic trading, fraud detection, credit risk assessment, customer service through chatbots, portfolio management, enhancing decision-making and risk management in the financial sector.

·       Autonomous Vehicles: AI powers self-driving cars, enabling them to navigate, detect obstacles, and make real-time decisions, potentially revolutionizing transportation and reducing accidents.

·       Natural Language Processing (NLP): NLP techniques are used in chatbots, virtual assistants, language translation, sentiment analysis, content generation, and more, facilitating human-computer communication and language-related tasks.

·       E-commerce and Marketing: AI aids in personalized product recommendations, customer segmentation, demand forecasting, and targeted advertising, leading to improved customer experiences and better marketing strategies.

·       Manufacturing and Industry: AI-driven robotics, automation, predictive maintenance, and quality control optimize manufacturing processes, leading to increased efficiency, reduced downtime, and enhanced product quality.

·       Education: AI can significantly impact the education domain by becoming the ideal personal tutor and having a significant influence on average kids. It will figure out the gaps, focus on addressing them and customizing instructions for the student.

·       Entertainment: AI is employed in video game development, content recommendation systems for streaming platforms, music composition, and special effects, enhancing entertainment experiences.

·       Cybersecurity: AI helps in detecting and responding to cyber threats by analyzing patterns, identifying anomalies, and predicting potential attacks, bolstering the security of digital systems and networks.

·       Agriculture: AI assists in crop monitoring, disease detection, yield prediction, and precision farming, optimizing resource utilization and increasing agricultural productivity.

·       Energy Management: AI is used in optimizing energy consumption, grid management, predictive maintenance of energy infrastructure, and renewable energy generation, contributing to more sustainable and efficient energy systems.

·       Computer Programming: Just by describing in plain English the purpose of the program, tools like CoPilot can quickly generate standard code in any programming language and thereby free up the programmer from writing run-of-the-mill programs and enable them to develop more complex and niche programs. 

 

These are just a few examples, and the applications of AI continue to expand across various industries as the technology evolves.

Human involvement as AI grows.

As Artificial Intelligence impacts every digital interaction of our lives and livelihoods, humans will play a critical role on many fronts. It is essential to understand that AI still needs the expertise of humans to finally pull the trigger. Even though things are going digital, and data driven, the decisions being made are for you or on your behalf, so they continue to be guard railed by the norms in that industry or society or professions.

·       Expertise – AI is based on inference engines and knowledge bases. Human expertise in defining the necessary and sufficient rules and constraints, developed empirically and intuitively by experts over decades forms the foundation of the inference engine, and decision making.

·       Efficiency - Technology will automate, remove the boring, painful manual jobs.AI will help humans to focus on more value-added fulfilling jobs, which leverage the higher skillset, more challenging and satisfying. Mundane work takes up unnecessary time; humans can deliver much more value focusing on high-skilled “brainier” work.

·       Involvement – Human involvement, learning from actions taken, helping with decision making are key to the success of AI. These are jobs which often lead to manual errors, which lead to more effort in reconciliation and fixing the errors.

o   Many of the uses highlighted above help businesses and people in processing humongous amount of data, run many complex models, weed out scenarios and help in decision making and taking the right action.

o   AI will help humans to do things like review results or scans and diagnose diseases or potential problems in the future. Diagnosis which would have been difficult for doctors based on just his knowledge, can be possible as computers leverage AI, much larger datasets, and rules.

o   Key is they use human’s expertise and knowledge to do things which was impossible for humans to do efficiently and then, deliver the results for humans to act on.

 

·       Bias – It’s critical to train AI models to eliminate obvious biases tied to individuals. Biases that exist in current algorithms and models can be better deciphered and rectified by a wider group involvement and continuous reviews of processes.

·       Validation – Humans are needed to validate the data and ensure the integrity of the data. They need to validate the models and the results and determine them to be suitable for action.

·       Decision making – AI will be a great tool to augment human decision-making. For example, an expert geoscientist, looking at 100 spreadsheets to decide on which field to explore, can now rely on AI and automation to process a million data sources, run complex models, and give the top 5 scenarios to consider. Humans still make the final decision, but it is based on many more data sets, scenarios, models, and complexities. AI will not make the final decision; humans will in many cases. For this balance to work, it is critical to know where AI is used and how any potential bias can be addressed.

·       Ethics and Empathy – One of the biggest concerns is AI going berserk without any human intervention, no consideration for human empathy, softer side of jobs, services, and interaction. Already significant investment is happening to put humans as arbitrators and, to research and model human features into AI models. AI cannot be an uncontrolled Frankenstein; it should be a better version of what humans could do alone but now can be achieved by working with humans. Humans can apply these softer skills, subjectively judge between options, and make the best use of AI. There should be a strong governance angle to this – where AI and its applications need to be monitored and proper oversight needs to be provided, like Asimov’s law of robots or Microsoft’s AI standards.

·       Augmented Intelligence – Finally, the combination of human and artificial intelligence created “Augmented Intelligence”. They close each other’s gaps; while AI processes more data, more models, and performs tasks automatically that humans cannot; human intelligence brings in empathy, subjectivity, validation, and many of the subjective mental inferences, machines may not be capable of.

 

Conclusion

Human intervention and natural intelligence must work together with Artificial Intelligence to bring the biggest value to humanity. Machines cannot be left to their uncontrolled will; humanity, empathy, and governance should be in place to monitor, control and pick the right uses of AI. That will impact the world, positively and for the greater good of humanity.