AI on HONOR: Power In Your Pocket, Responsibility in Our Hands
Posted: Wed Apr 17, 2024 10:27 am
At HONOR, our mission is to build cutting-edge, potent technology that gives you control and empowers you. But with great power comes great responsibility, especially when it comes to Artificial Intelligence (AI).
AI is quickly altering every aspect of our lives, from the way we shop to how we interact with our phones. But AI isn't magic- it's built on data, and data can be biased.
Algorithmic Bias: Biased algorithms lead to unfair outcomes (think biased hiring decisions or discriminatory loan approvals).
Trust Erosion: Users lose trust if they perceive bias in AI decisions.
Legal Implications: Discriminatory AI violates anti-discrimination laws.
Consider an AI that suggests stories from the news. Your worldview may be limited by the AI's suggestion if the training data primarily consists of articles written from a single point of view. This is an example of bias in action.
Bias in AI can lead to unfair outcomes like loan applications being rejected for no good reason. Additionally, it may perpetuate preconceptions, which isn't exactly the inclusive society we aim to create.
Data Diversity: We train our AI on a wide range of data sets to make sure it accurately represents the actual world.
Human Oversight: To identify and address prejudice, experts examine AI judgments.
Transparency: You can trust our AI since we're upfront about its workings.
CERT-In plays a similar role in the domain of cybersecurity. It is the national nodal agency which is responsible for responding to computer security incidents in India. CERT-In gathers, analyzes, and disseminates information on cyber incidents, issues alerts, and coordinates incident response activities. Just like data diversity, human oversight, and transparency are crucial in ensuring an unbiased and secure digital environment. Together, we strive to create a safer and more inclusive technological landscape. Learn more about CERT-In on their official website CERT-In
But here's the thing: Mitigating bias is an ongoing process. We need your help!
:
AI is quickly altering every aspect of our lives, from the way we shop to how we interact with our phones. But AI isn't magic- it's built on data, and data can be biased.
Data Bias: AI learns from historical data. If that data contains biases(gender, race, etc.), the AI perpetuates them.The Bias Quandary
Algorithmic Bias: Biased algorithms lead to unfair outcomes (think biased hiring decisions or discriminatory loan approvals).
Inequitable Outcomes: Biased AI can aggravate existing inequalities.What's the Big Deal About Bias?
Trust Erosion: Users lose trust if they perceive bias in AI decisions.
Legal Implications: Discriminatory AI violates anti-discrimination laws.
Consider an AI that suggests stories from the news. Your worldview may be limited by the AI's suggestion if the training data primarily consists of articles written from a single point of view. This is an example of bias in action.
Bias in AI can lead to unfair outcomes like loan applications being rejected for no good reason. Additionally, it may perpetuate preconceptions, which isn't exactly the inclusive society we aim to create.
At HONOR, our goal is to create moral artificial intelligence. Here are some ways we're tackling bias:So, How Do We Make AI Fairer?
Data Diversity: We train our AI on a wide range of data sets to make sure it accurately represents the actual world.
Human Oversight: To identify and address prejudice, experts examine AI judgments.
Transparency: You can trust our AI since we're upfront about its workings.
CERT-In plays a similar role in the domain of cybersecurity. It is the national nodal agency which is responsible for responding to computer security incidents in India. CERT-In gathers, analyzes, and disseminates information on cyber incidents, issues alerts, and coordinates incident response activities. Just like data diversity, human oversight, and transparency are crucial in ensuring an unbiased and secure digital environment. Together, we strive to create a safer and more inclusive technological landscape. Learn more about CERT-In on their official website CERT-In
But here's the thing: Mitigating bias is an ongoing process. We need your help!
:
Here are some questions to spark a conversation:Let's Talk!
- Have you ever encountered biased AI in your daily life?
- How can we ensure AI is used for good , not harm?
- What role do you think consumers play in ethical AI development?
