How are AI and the future of mankind mutually dependent on each other?

AI or Artificial intelligence has emerged as the best competitor for “human” jobs. Whether it is in translating languages, inventories management, diagnosing disease, logistics, or providing customer service, AI is present and evolving at a far more speed than the human race can imagine! And, with unsupervised AI learning algorithms, the fear that AI will take over human jobs to replace workers in all segments of the automation-driven economy is no longer a mere irrational human fear! 

This is in some ways the inevitable outcome of the super-fast algorithms, growth of very Big Data, the NLP- Natural Learning Processing, Deep Neural Networks, ML- Machine Learning, and more. But, with all the responsive digital and technological tools humans use, AI is set to change who does the work and how it gets done. However, the ultimate goal of artificial intelligence is to augment and complement the capabilities of humans and not to replace human workers.

The need for AI and humans to work collaboratively: 

In the report by Harvard Business Reviews on 1,075 companies, the findings are eye-opening and encouraging. A large number of companies have automated their production processes. But, only those who look at extremely short-time gains seek to use AI to replace employees. Firms that sought to use AI as a complementary collaborative intelligence recorded significant productivity improvements that retained humans’ social, leadership, and teamwork skills while using quantitative, scalability, and speed of artificial intelligence. Machines and algorithms cannot figure out empathy, a joke, or compassion, while humans cannot replicate the AI speed, data handling, or adaptability of artificial intelligence.

 Human intervention is crucial:

In assisting machines, three roles cannot replace human intervention. They are in

• Training the ML algorithms
• Explaining the ambiguity in predictions, forecasts, and outcomes of AI
• Sustain the responsible use of machines.

Training advances: Machine-learning ML algorithms are trained extensively to do the things they do. The human being is thus a trainer and vital to del with handling data for the algorithms to help make financial decisions, help apps detect medical diseases, or teach machines to use Natural Learning Processing-NLP applications. For example, Alexa, Siri, Cortana, etc., the AI apps needed a long training period to develop their personalities and behavior. And, though AI assistants display subtle traits of humans, they are not intuitive in feelings. Again, the bot may erroneously react to stress as a positive emotion that needs action!

Explaining the results: The trends, forecasts, predictions, and conclusions drawn by AI devices need experts to explain the algorithm behavior outcome to non-users and non-expert users. Here, the role of humans as a translator for opaque processes. For example, how the AI came to predict a particular disease or inputs of weighed evidence-based data like law analysis. And, it is not just the regulated industries but also all consumer-facing algorithm industries that need such explainers. For example, how did the algorithm compute the penal fee if the date was extended? This area does not replace human beings. Rather it augments the need for skilled human workers, thereby increasing the employment rate. This is expected to create over 75,000 jobs to cater to the GDPR- General Data Protection Regulation requirements in just the European Union!

Sustaining machine use: In addition to having people, who can explain AI outcomes, companies need “Sustainers” who are humans to ensure the AI functions safely, responsibly, and properly and not, for example, to trigger dangerous events. 

Control over Artificial Intelligence is vital to humans:

An Introduction to Artificial Intelligence shows that AI- applications till now have boosted decision-making, analytic and creative abilities in humans. For example, many expert safety engineers track, forecast, and predict when AI can turn harmful. Humans are needed to work on the industrial robots, review explainer analysis when self-driven cars meet with accidents, etc. A team of ‘ethics managers works to sustain and ensure the ethical use of artificial intelligence in applications. Again consider AI use in credit approval systems being discriminatory. In data-related roles of AI, humans are required to ensure AI use is responsible and manages the data properly and confidentially. Consider the example of banks and several companies that use and collect client information. The human is vital to ensure that AI enhances customer experience and does not use data collected indiscriminately. Such use is illegal, discriminatory, and a breach of privacy.

AI Machines Assist Humans:

Smart machines are expanding human capabilities in three tasks. They 

• Amplify cognitive ability
• Interact with employees and customers to free time for other tasks.
• Extend human capabilities.

Amplify cognitive ability:

AI is used to heighten creativity, speed up decisions and enhance analytical abilities by providing the needed inputs at a specific or opportune moment. For example, designers use AutoDesk AI in the Dream Catcher app to heighten creative designs through inputs on the designer’s needs. It then makes its calculations, matches innumerable designs, and ensures the dream product is caught by the designer. Thus, aesthetic sensibilities, calculations, professional judgment, and design criteria are easily imparted.

Human Interactions:

Bots and virtual assistants using AI and NLP have made human-to-machine collaboration possible in more efficient and effective ways. For example, voice searches, banking inquiry bots, etc., can process thousands of searches in customer service simultaneously, while Alexa, the virtual assistant, can perform routine tasks like switching off lights. 

Embodying human capabilities:

Cortana, the Microsoft digital assistant, is a virtual digital entity with human-like traits embodied in it using NLP to help understand and execute simple commands. They use motors, sensors, actuators, and AI to work and simplify human lives. In industrial applications, the cobot (context-aware robot) does the heavy lifting leaving the humans to assemble critical processes involving skill, talent, decision making, etc. 

Conclusion: 

The above article proves AI is a blessing and not the bane of technology if used properly and collaboratively with humans. Studying all about ML and AI can make you an expert in your chosen career, fetching you mind-boggling salaries. But, this is skill-dependent.

You, too, can become an ace with Great Learning’s MTech in Artificial Intelligence program, which both working professionals and students with a BE can undertake online. The program helps acquire hands-on skills in industry-relevant applications through effective experiential learning. Enroll today!