DGP: AI untuk Rakyat

When a machine can mimic human intelligence, it is termed as artificially intelligent.

In other words, an AI machine has human-like abilities to solve real-world problems, improvise based on its learnings and experiences, make predictions according to the information it has and make decisions on its own.

- Artificial Intelligence has been revolutionizing industries and economies.

- While AI seems to be pretty sci-fi and out of our reach, it is a technology that has been impacting our lives for a long time now.

- There are a variety of applications and tools powered by AI that help us in our day-to-day lives.

- Eg: Waze, Google Maps, Google Assistant or Siri. These are applications powered by AI.

AI has come up as a vital resource in our fight against the COVID-19 pandemic.

As you know, COVID-19 can be transmitted through direct, indirect, or close contact with infected individuals.

AI can play a vital role in analyzing these data accurately to track and protect everyone.

AI can assist in contact tracing by gathering and analyzing huge population data about health, location, and timing.

AI can assist doctors to treat patients with minimal contact.

AI can also assist to prescribe the correct course of treatment for patients.

How do machines learn?

- Machines are fed with data, which is the information used to build the foundation of their intelligence.

- Machines are trained on this data and they develop their own understanding around it in the form of algorithms.

- Once the machine starts functioning, it keeps on updating its algorithm according to its own experiences.

- Just like us, machines also gather feedback on the mistakes they have made and improvise accordingly.

Here’s how this actually happens:

- The machine collects data - Data Acquisition

- It analyses the data to find patterns – Data Exploration

- It tries out different solutions- Solution Modeling

- Receives feedback and figures out the best solution - Evaluation

- It implements the optimal solution – Deployment

AI Domains: An Introduction

- Machine gets its decision-making abilities after recognizing patterns and trends from the data during its training process.

- Since AI has a wide variety of applications, we divide the entire field into sub-fields called the Domains of AI.

Statistical Data: An Introduction

- AI applications that fall under the domain of Statistical Data deal with numeric or alpha-numerical datasets.

- You must have encountered data being collected in the form of series or tables. For example, attendance data, booking data, expense statements, etc.

Responsible AI principles/ethics.

Why do we need ethics:

- Ethics are the code of conduct to use AI and eliminate or reduce AI abuse.

- It is vital to keep a check on how humans are using AI.

- AI can do spectacular things if it is provided with the required data and quality training.

- Keeping AI within controlled limitations through codes of conduct will help us use it for good.

Key take-outs

AI is helping industries in their growth.

We learned how the three AI domains help us understand what kind of data AI deals with.

Statistical Data helps AI analyze numerical data and give better predictions.

Similarly, Natural Language Processing (NLP) helps computers communicate with us.

The last domain of AI, Computer Vision, is literally what it stands for: it is the vision of computers.

Computers learn what they are taught. Biases can creep into algorithms if the data provided to them is biased, to begin with.