Answer:

Introduction:

The use of online methodology for day-to-day meetings, institutional approvals, and education has become increasingly popular, especially during the pandemic. While it offers numerous advantages such as convenience, accessibility, and cost-effectiveness, it also presents ethical issues, particularly when it comes to the vulnerable sections of society.

Body:

Ethical issues involved in digitisation :-

• Inequitable Access: Limited internet access and technological infrastructure disproportionately affect vulnerable sections, such as rural communities, tribal populations, and economically disadvantaged individuals, widening the digital divide.
  • Example: Lack of internet connectivity in remote villages hinders access to online education resources, leaving marginalized students at a disadvantage.
• Exclusion of Non-Digital Natives: Older adults and individuals with limited digital literacy may struggle to adapt to online systems, leading to their exclusion from essential services and opportunities.
  • Example: Senior citizens, particularly those from marginalized backgrounds, face challenges in accessing online healthcare consultations due to limited technological proficiency.
• Cybersecurity Risks: Vulnerable individuals may fall victim to online fraud, data breaches, or identity theft, compromising their privacy and financial well-being.
  • Example: Phishing scams targeting unsuspecting individuals, including senior citizens, can lead to financial losses and personal information misuse.
• Online Harassment and Exploitation: Vulnerable groups, such as women, children, and LGBTQ+ individuals, may face increased risks of online harassment, cyberbullying, and exploitation.
  • Example: Instances of online stalking and harassment of women on social media platforms highlight the need for robust safeguards and mechanisms to protect vulnerable individuals.
• Bias and Discrimination: Online algorithms and automated decision-making systems may perpetuate biases and discrimination, affecting vulnerable populations, such as marginalized communities and ethnic minorities.
  • Example: Biased facial recognition technology that disproportionately misidentifies individuals with darker skin tones can lead to discriminatory outcomes in law enforcement and public surveillance.

Conclusion:

It is also important to be aware of the potential biases and discrimination that can arise and to take steps to mitigate them. Ultimately, the use of online methodology should be guided by ethical principles such as fairness, respect for privacy, and concern for the well-being of all individuals involved.

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