Question:
Directions (1-10): Read the following passage carefully and answer the questions given below it.
Artificial Intelligence (AI) and machine learning are rapidly transforming the financial sector. While traditional banking heavily relied on human interaction and manual processing, digitalization has ushered in an era where algorithms predict consumer behavior, assess credit risks, and even execute trades in milliseconds. The primary drivers for this shift are the vast amounts of data generated daily and the need for personalized customer experiences. Banks are deploying chatbots for customer service, reducing operational costs and providing 24/7 assistance. However, this rapid integration is not without challenges. Data privacy concerns and the potential for algorithmic bias pose significant risks. If an AI model is trained on historical data that reflects past prejudices, it may inadvertently deny loans to qualified candidates from marginalized communities. Furthermore, the opacity of deep learning models, often referred to as ‘black boxes’, makes it difficult for regulators to audit decision-making processes. As the financial landscape evolves, regulatory frameworks must adapt to ensure that innovation does not compromise stability or fairness.
Q2. Which of the following risks is associated with AI integration according to the passage?
(a) Excessive human interaction
(b) Algorithmic bias
(c) Slower transaction speeds
(d) Increased transparency
(e) Manual processing errors
Directions (1-10): Read the following passage carefully and answer the questions given below it.
Artificial Intelligence (AI) and machine learning are rapidly transforming the financial sector. While traditional banking heavily relied on human interaction and manual processing, digitalization has ushered in an era where algorithms predict consumer behavior, assess credit risks, and even execute trades in milliseconds. The primary drivers for this shift are the vast amounts of data generated daily and the need for personalized customer experiences. Banks are deploying chatbots for customer service, reducing operational costs and providing 24/7 assistance. However, this rapid integration is not without challenges. Data privacy concerns and the potential for algorithmic bias pose significant risks. If an AI model is trained on historical data that reflects past prejudices, it may inadvertently deny loans to qualified candidates from marginalized communities. Furthermore, the opacity of deep learning models, often referred to as ‘black boxes’, makes it difficult for regulators to audit decision-making processes. As the financial landscape evolves, regulatory frameworks must adapt to ensure that innovation does not compromise stability or fairness.
Q2. गद्यांश के अनुसार AI एकीकरण से जुड़ा निम्नलिखित में से कौन सा जोखिम है?
(a) अत्यधिक मानवीय संपर्क
(b) एल्गोरिथम पूर्वाग्रह
(c) धीमी लेनदेन गति
(d) बढ़ी हुई पारदर्शिता
(e) मैन्युअल प्रोसेसिंग त्रुटियां
Correct Answer: (b)
Explanation:
Detailed Explanation: The passage mentions data privacy concerns and the potential for algorithmic bias as significant risks.
विस्तृत व्याख्या: गद्यांश डेटा गोपनीयता संबंधी चिंताओं और महत्वपूर्ण जोखिमों के रूप में एल्गोरिथम पूर्वाग्रह की क्षमता का उल्लेख करता है।