# The Future We Build With AI | KASHIKA JAIN | TEDxShiva Shiksha Sadan Youth

Source: https://www.youtube.com/watch?v=Op4MsF-nIxg
Recap page: https://rapidrecap.app/video/Op4MsF-nIxg
Generated: 2025-11-11T22:07:15.579+00:00

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## Quick Overview

Kashika Jain argues that the future of Artificial Intelligence (AI) involves humans growing alongside AI, emphasizing that AI is not inherently perfect but rather a powerful tool that learns from human biases and data, necessitating ethical responsibility from the youth generation to shape its future development, including advancements in Quantum Computing and NLP.

**Key Points:**
- Kashika Jain, a Final Year B.Tech student and AI enthusiast, delivered a TEDx talk titled "The Future We Build With AI." (00:01)
- She defines AI as an umbrella term that includes Machine Learning, which further consists of Supervised, Unsupervised, Deep, and Reinforcement Learning, plus Transformers and Quantum AI. (00:48)
- The speaker stresses that Deep Reinforcement Learning combines cognitive abilities of the brain with learning through trial and error to create AI agents capable of complex behaviors. (01:44)
- AI systems, like large language models (LLMs) such as ChatGPT, are not perfect; they often reproduce biases and stereotypes present in the real-world data they are trained on. (01:54, 08:10)
- The future of AI is not about robots taking over, but about humanity growing up with AI, utilizing tools like NLP and Quantum Computing to solve global issues like climate change. (09:12, 09:51)
- Quantum computing, which replaces bits with qubits, will drastically increase the speed and accuracy of computers, allowing them to solve complex mathematical equations that current computers cannot. (07:52, 08:01)

![Screenshot at 00:55: Kashika Jain presents a Venn diagram illustrating the relationship between Artificial Intelligence, Machine Learning, and various sub-fields like Supervised Learning, Deep Learning, Transformers, and Quantum AI, establishing the technical scope of her discussion.](https://ss.rapidrecap.app/screens/Op4MsF-nIxg/00-00-55.png)

**Context:** This video captures a TEDx talk by Kashika Jain, a final-year B.Tech student specializing in Data Science, delivered at the TEDx Shiva Shiksha Sadan Youth event. Her presentation focuses on the current state and future trajectory of Artificial Intelligence (AI), contrasting the common fear of AI replacing humans with her vision of co-existence and emphasizing the ethical responsibilities young developers hold in shaping unbiased AI.

## Detailed Analysis

Kashika Jain opens by establishing her credentials as a B.Tech student and AI enthusiast before immediately challenging the narrative of AI as a master, quoting Mark Zuckerberg's sentiment that the younger generation must be the collaborator, not the master. She then breaks down the AI landscape, showing that Machine Learning is a subset of AI, which includes specific areas like Deep Reinforcement Learning (DRL), which mimics human learning through trial and error to solve complex problems like optimizing traffic light systems. Jain highlights that DRL aims to maximize cumulative rewards by learning from success and failure. She transitions to discussing the limitations of current AI, specifically pointing out that models like ChatGPT inherit the biases and stereotypes present in their training data, illustrating this with the example of how an AI might assign more attention to certain words based on historical biases. Looking ahead, she addresses Quantum Computing, noting that it will replace bits with qubits, exponentially increasing computational speed and accuracy, allowing for solving problems currently intractable for classical computers. She concludes by asserting that the future is about humans and AI growing together ethically, stressing that the youth must take responsibility to ensure AI is built fairly and contributes positively to solving global challenges like climate change, rather than simply replacing human effort.

### Introduction & AI Landscape

- Kashika Jain introduces her theme, 'The Future We Build With AI'
- AI is an umbrella term encompassing Machine Learning
- ML includes Supervised, Unsupervised, Deep, and Reinforcement Learning, plus Transformers and Quantum AI. (00:06-00:54)

### Deep Reinforcement Learning (DRL) Applications

- DRL combines brain cognition with trial-and-error learning
- Used to create AI agents that learn complex behaviors
- Example: Optimizing traffic light systems by maximizing cumulative rewards. (01:21-02:50)

### The Imperfection of AI

- AI is not perfect and reflects societal biases present in training data
- ChatGPT examples show models misunderstanding context or producing nonsense
- AI is a tool that needs ethical guidance. (08:06-09:02)

### Future of AI

- Quantum Computing will replace bits with qubits, enabling exponential speed and accuracy
- Computers will solve complex mathematical equations currently unsolvable
- The goal is not AI takeover but collaborative growth. (07:15-08:05, 10:10-10:18)

### Call to Action for Youth

- The youth generation has the responsibility to ensure the future of AI is ethical and fair
- AI can be utilized to find solutions for global issues like climate change. (08:40-09:56)

![Screenshot at 00:01: Introduction slide displaying speaker name, Kashika Jain, and her credentials as a Final Year B.Tech Student & AI Enthusiast.](https://ss.rapidrecap.app/screens/Op4MsF-nIxg/00-00-01.png)
![Screenshot at 00:55: Venn diagram illustrating the hierarchy and overlap between Artificial Intelligence, Machine Learning, and its sub-fields \(Supervised, Deep, Reinforcement Learning, Transformers\).](https://ss.rapidrecap.app/screens/Op4MsF-nIxg/00-00-55.png)
![Screenshot at 01:29: Slide focusing on Deep Reinforcement Learning, emphasizing its combination of cognitive ability and trial-and-error learning.](https://ss.rapidrecap.app/screens/Op4MsF-nIxg/00-01-29.png)
![Screenshot at 03:34: Slide highlighting the application of DRL in real-world scenarios, specifically in optimizing traffic light systems \(red and green lights\).](https://ss.rapidrecap.app/screens/Op4MsF-nIxg/00-03-34.png)
![Screenshot at 04:05: Slide introducing Generative AI and mentioning specific models like Chat GPT and LLMs \(e.g., Llama 3\) as examples of Transformer-based AI.](https://ss.rapidrecap.app/screens/Op4MsF-nIxg/00-04-05.png)
![Screenshot at 05:23: Slide focusing on Natural Language Processing and Sentiment Analysis, core areas where AI learns human language nuances.](https://ss.rapidrecap.app/screens/Op4MsF-nIxg/00-05-23.png)
![Screenshot at 08:09: Slide declaring the key thesis: "AI IS NOT PERFECT," setting up the discussion about inherent biases.](https://ss.rapidrecap.app/screens/Op4MsF-nIxg/00-08-09.png)
![Screenshot at 09:12: Slide titled "GROWING WITH AI," pivoting the narrative from fear of takeover to collaboration.](https://ss.rapidrecap.app/screens/Op4MsF-nIxg/00-09-12.png)