How Artificial Intelligence is Shaping the Future of Work: Part 2
Tags: ai, development, machinelearning, programming
Published: 2023-09-16 21:10:06

## Four Types of Artificial Intelligence




**1. Reactive machines:** These AI systems have no memory and are task-specific. An example is Deep Blue, the IBM chess program that beat Gary Kasparov in the 1990s


**2. Limited memory:** These AI systems have a memory so they can use past experiences to inform future decisions.


**3. Theory of mind:** It is a psychological term. When applied to AI, it means that the system 
would have the social intelligence to understand emotions.


**4. Self-awareness:** In this category, AI systems have a sense of self, which gives them consciousness. Machines with self-awareness understand their current state. THIS TYPE OF AI does not yet exist.
Examples of AI technology and how it is used today:



## Automation



When paired with AI technologies, automation tools can expand the volume and types of tasks performed. An example is robotic process automation (RPA), a type of software that automates repetitive rules-based data processing tasks traditionally done by humans. When combined with machine learning and emerging AI tools, RPA can automate bigger portions of enterprise jobs, enabling RPA’s tactical bots to pass along intelligence from AI and respond to process changes.



## Machine learning



 The science of getting a computer to act without programming. Deep learning is a subset of machine learning that in very simple terms, can be thought of as the automation of predictive analytics.


**Types of machine learning:** supervised learning, unsupervised learning, reinforcement learning



## Machine vision



This technology gives a machine the ability to see. Machine vision captures and analyzes vision information using a camera, analog-to-digital conversation, and digital signal


## Natural language processing (NLP)


 This is the processing of human language by a computer program. One of the older and best-known examples of NLP is spam detection which looks at the subject line and text of an email and decides if it’s junk. Current approaches to NLP are based on machine learning. NLP tasks include text translation, sentiment analysis, and speech recognition.



## Robotics

 
This field of engineering focuses on the design and manufacturing of robots. Robots are often used to perform tasks that are difficult for humans to perform or perform consistently. For example, robots are used in assembly lines for car production or by NASA to move large objects in space. 



## Self-driving cars


Autonomous vehicles use a combination of computer vision, image recognition, and deep learning to build automated skills at piloting a vehicle while staying in a given lane and avoiding unexpected obstructions such as pedestrians.



## Where can AI be applied



**- AI in healthcare:** The biggest bets are on improving patient outcomes and reducing costs. Companies are applying machine learning to make better and faster diagnoses than humans. One of the best-known healthcare technologies is IBM Watson. It understands natural language and can respond to questions asked of it. There are also online health virtual assistants.


**AI is used to diagnose and treat diseases.**
For example, IDx-DR is the first-ever autonomous AI system that instantly detects the condition. With the backing of the US Food and Drug Administration (FDA) to provide diagnostic support, it detects signs of diabetic retinopathy in ocular images and then uses an algorithm to create a binary diagnosis in minutes. AI can be extensively used in treating cardiovascular diseases as well.

Brain-computer interface
Next generation of radiology tools 
Fill shortages of trained healthcare provides


**- AI in business:** Machine learning algorithms are being integrated into analytics and customer relationship management (RM) platforms to uncover information on how to better serve customers. Chatbots have been incorporated into websites to provide immediate service to customers.


**- AI in education:** AI can automate grading educators more time. It can assess students and adapt to their needs, helping them work at their own pace. AI tutors can provide additional support to students, ensuring they stay on track.


**- AI in finance:** AI in personal finance applications such as Intuit Mint or Turbotax is distributing financial institutions. Other applications like IBM Watson have been applied to the process of buying a home.


**- AI in law:** AI can be used to automate the legal industry’s labor-intensive processes save time and improve client service.


**- AI in manufacturing:** Manufacturing has been at the forefront of incorporating robots into the workflow. For example, the industrial robots that were at one time programmed to perform single tasks and separated from human workers, increasingly function as cobots.


**- AI in banking:** AI virtual assistants are being used to improve and cut the cost of compliance with banking regulations.


**- AI in transportation:** AI is used in transportation to manage traffic, predict flight delays, and make ocean shipping safer and more efficient.


**- Speech recognition:** Also known as automatic speech recognition(ASR), computer speech recognition, or speech-to-text, it is a capability that uses natural language processing (NLP) to process human speech into a written format. Many mobile devices incorporate speech recognition into their systems to conduct voice searches e.g. Siri or provide more accessibility around texting.


**- Customer service:** Online virtual agents are replacing human agents along the customer journey. They answer frequently asked questions(FAQs) around topics like shipping or providing personalized advice, cross-selling products, or suggesting sizes for users changing the way we think about customer engagement across websites and social media platforms. 


**Examples include messaging bots on e-commerce sites** with virtual agents, messaging apps, such as Slack and Facebook Messenger, and tasks that are usually done by virtual assistants and voice assistants.


**- Computer vision:** This enables computers and systems to derive meaningful information from digital images, videos, and other visual inputs, and based on those inputs, it can take action. This ability to provide recommendations distinguishes it from image recognition tasks. Powered by convolutional neural networks, computer vision has applications within photo tagging in social media, radiology imaging in healthcare, and self-driving cars within the automotive industry.


**- Recommendation engines:** Using past consumption behavior data, AI algorithms can help discover data trends that can be used to develop more effective cross-selling strategies. This is used to make relevant add-on recommendations to customers during the checkout process for online retailers.


**- Automated stock trading:** Designed to optimize stock portfolios, AI-driven high-frequency trading platforms make thousands or even millions of trades per day without human intervention.


**- Security:** AI can provide alerts to new and emerging attacks much sooner than human employees and previous technology iterations.



## Augmented intelligence vs. artificial intelligence



**- Augmented intelligence:** Some researchers and marketers hope the label augmented intelligence, which has a more neutral connotation will help people understand that most implementations of AI will be weak and simply improve products and services. 


**- Artificial intelligence:** True AI or artificial general intelligence is closely associated with the concepts of technological singularity. A future ruled by an artificial superintelligence that far surpasses the human brain’s ability to understand it or how it is shaping our reality.

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