Emerging technologies and their legal challenges

 Try to emulate the human brain

Artificial intelligence, in its broadest sense, refers to the intelligence demonstrated by computers, particularly computer systems that aim to emulate the human brain. This branch of computer science study creates software that allows machines to process their surroundings and use information for learning and intelligence, hence increasing the likelihood of achieving a specific goal.

It interacts via human speech

Advanced web search engines, such as Google Search, are some well-known examples of AI applications. It uses recommendation methods similar to those used by Netflix, YouTube, and Amazon. It also communicates via human speech, as seen in Alexa, Siri, and Google Assistant. Autonomous vehicles are another application, as are generative and creative technologies like ChatGPT and AI art.

Traditional goals of artificial intelligence

When we look at the conventional goals of artificial intelligence and its research, we can see that they include planning, learning, natural language processing, vision, knowledge representation, reasoning, and robotics support.

Moving on to understanding how OpenAI's latest AI model, Strawberry, claims to achieve an advanced level of artificial intelligence in terms of large language model reasoning capabilities, despite raising serious concerns about artificial intelligence's efficiency and potential risks.

Significant excitement among young people

OpenAI just published its latest artificial intelligence models, O1 Preview and O1 Mini, popularly known as Strawberry. These models are predicted to represent substantial advances in artificial intelligence technology, notably in the reasoning skills of huge language models.

What is the connection between the strawberry's mother and starting a GPT chat? Young people are really excited about the novelty, efficiency, and potential difficulties that artificial intelligence might provide.

This methodology employs an intriguing model that is used by humans. Have you ever tried jotting down every step you take when addressing an issue in a notebook? Artificial intelligence employs a similar capacity known as chain of thought thinking. This reasoning is similar to how humans solve problems by dividing down big jobs into many smaller, more manageable subtasks.

The processes we're discussing, known as chain of thought reasoning, are now used by AI systems. It was not a deliberate decision, but during a 2022 study, some researchers discovered that chain of thought reasoning can be used by artificial intelligence.

Launch of Opining for strawberry

These scholars are Google researchers and colleagues from the University of Tokyo who have used the concept of chain of thought in artificial intelligence.

The procedure improves the artificial intelligence system.

The dispute around the use and fresh launch of Opining for strawberry has caused considerable confusion. Many specialists in the industry have wondered what approaches and models this artificial intelligence uses, some of which are known as self-verification. This approach improves the artificial intelligence system's capacity to follow a path of reasoning that is akin to human cognition.

Let us now realize that when we picture anything, our brain attempts to undertake cell verification before applying that reasoning in actual life. First and foremost, we have an idea, which we then put into action. A similar model will be used for artificial intelligence.

Artificial intelligence is a powerful and transformational instrument that carries inherent hazards, notably due to its lack of transparency in operation. Simply put, the operation of artificial intelligence is not very apparent.

The self-verification process of artificial intelligence contains some opaque patches.

Does artificial reasoning or decision-making work?

What does it indicate when an artificial intelligence model is unable to offer its users with knowledge about how the system, artificial reasoning, or decision-making works? This results in a grey area that lacks transparency. This lack of visibility affects trust and accountability in artificial intelligence by preventing people from verifying the rationale behind the model's output or improving it through input.

Cannot be validated

One of the characteristics of artificial intelligence is that the data it generates is inaccessible for inspection or customisation, as artificial intelligence models provide output that cannot be checked. We have no idea what strategies the model uses or how much it consumes.

Errors in logic or accuracy.

That is a significant barrier for artificial intelligence because we cannot fix any errors, have no method to refine deduction, and have no idea how to direct the system to specific demands. What does it implement? It can directly raise issues about misinformation, as users have no method of detecting erroneous logic or inaccuracy.

1. Data Security – Growing concerns over data breaches, encryption, and compliance with evolving regulations.

2. Big Data - Challenges in data collection, analytics, security, and ownership.

3. Cloud Computing: Cost savings against increased dangers to data privacy and security.

4. Open Source Software - Compliance problems and the danger of losing software ownership.

5. Mobile Payments - Concerns about misdirected payments and unauthorized access.

6. Social Media Liabilities: Legal risks associated with online promotions, marketing compliance, and content rights.

7. Wearable Computing - Privacy and security concerns about biometric and mobile device integration.

8. The Internet of Things (IoT) - Privacy concerns stem from tracking and data collecting from linked devices.

9. Virtual currency - Legal and security challenges for decentralized digital currency.

10. Remote Automation and Control - Liability issues with smart home, office, and city automation.