The rise of the machines is becoming an impending reality. The Artificial Intelligence (AI) revolution is here. Most businesses are aware of this and see the tremendous potential of AI.
In this short article we defines AI and explains the 3 basic forms of AI:
- Assisted Intelligence
- Augmented Intelligence
- Autonomous Intelligence
The Artificial Intelligence (AI) revolution is here. Businesses are aware of this and see the tremendous potential of AI. However, they are not ready to take advantage of this emerging Digital technology.
A “Digital IQ” survey of senior executives worldwide conducted by PwC in 2017 revealed that 54% of respondents stated they were making significant investments in AI. However, only 20% said their organizations had the necessary skills to succeed with this technology.
AI will affect the nature of activities, such as:
- Collaboration
- Enterprise structures
- Decision making
- Research and development
- Creative/artistic processes
Assisted Intelligence
Assisted Intelligence improves what people and organizations are currently doing.
In other words, it amplifies the value of existing activities. It is currently widely available and deployed
- Assisted Intelligence typically involves clearly defined, rule-based, and repeatable activities.
- Examples include:
−Robotic Process Automation (RPA) – RPA is process automation technology where software-based workers simulate routine human activities.
−Physical robots (e.g., automated assembly lines).
−Back-office functions (e.g. billing, finance, regulatory compliance).
−Enterprise software processes (e.g. order-to-cash, opportunity-to-order).
- Assisted Intelligence applications also include modeling of complex realities, so that organizations can test decision and scenarios with less risk.
Augmented Intelligence
Augmented Intelligence enables people and organizations to do things they otherwise
couldn’t do. It does this by giving new capability to human activity. It is emerging today
- To develop applications based on Augmented Intelligence, we need to imagine products, services, or processes that would not be possible at all without AI.
- Augmented Intelligence applications are typically based on Machine Learning (ML) and Natural Language Generation (NLG) algorithms, which are custom developed for our organization’s use case or our industry
−ML provides computers with the ability to learn and self-improve. These algorithms identify patterns in structured data.
−NLG generates natural language from a machine representation system, such as a knowledge base or a logical form. In other words, it translates data into a natural language representation.
- To measure the success of Augmented Intelligence implementations, we can track our margins, innovation cycles, customer experience, impact on disruption, and revenue growth as potential metrics.
Autonomous Intelligence
Autonomous Intelligence creates and deploys machines that act on their own. It is being
developed for the future. Although there are working examples, there are no pervasive deployments.
- Autonomous Intelligence systems have not become widespread, but will spearhead the Fourth Industrial Revolution (4IR).
- Early working examples include:
−Automated trading in the stock market. In fact, about 75% of Nasdaq trading is conducted autonomously. The new breed of high-frequency trading firms are largely based on this form of AI.
−Facial recognition.
−Autonomous vehicles. Elon Musk says by the end of 2017, Telsa will have an autonomous car that can drive from Los Angeles to New York.
−Medical diagnosis (mostly by examining medical images, e.g. x-rays).
−Bomb disposal robots.
−Space station maintenance.
−Gathering of deep-sea data.
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