ITGS News Analysis: Stakeholders, Systems & Ethical Impacts

March 11, 2025

By Mohsin Khurshid

Task Description: Find two ITGS related news articles. Analyse them and describe: the key stakeholders, the IT systems involved, and the area of application (Business, Health, Politics, Home & Leisure, Education, Environment). Explain the social impacts and ethical issues caused by the technology – aim for a mix of positive and negative social impacts.

Solution:

With the rapid advancement of information technology, its usage has expanded across various sectors, enhancing efficiency and productivity. For instance, banks utilize IT for seamless record management, while numerous industries incorporate IT solutions to optimize their operations. However, along with its benefits, information technology also raises social and ethical concerns. This article examines two ITGS-related news articles published by BBC, analyzing their key stakeholders, IT systems involved, areas of application, and the associated social and ethical impacts including both positive and negative.

1. Live facial recognition surveillance ‘must stop’ (Nye, 2019)

This article, published by Catrin Nye on BBC, discusses the use of live facial recognition (LFR) technology by UK police for security and surveillance.

Key Stakeholders

The stakeholders affected by this technology include:

The public – individuals who are monitored by facial recognition systems.
Law enforcement agencies – police officers and security officials utilizing the system.
Policymakers and government officials – those responsible for implementing regulations and policies regarding the use of facial recognition.
Privacy advocates and human rights organizations – groups concerned about the ethical implications of mass surveillance.

IT System and Area of Application

Technology Used: Facial recognition software integrated with surveillance cameras.
Application Area: Security and law enforcement.

How the System Works

This facial recognition system captures images of individuals passing through surveillance cameras. The captured images are then compared with a police database of wanted criminals. If a match is found, law enforcement is alerted, and the suspect can be detained.

Positive Social Impacts

Enhanced security: This system improves public safety by helping police identify criminals and prevent crimes.
Crime prevention: Law enforcement can intercept known terrorists or fugitives, preventing potential threats before they occur.

Negative Social and Ethical Concerns

Privacy violations: The system continuously scans individuals without their consent, raising ethical concerns about surveillance and mass data collection.
Risk of misidentification: The technology may not always be accurate, particularly when identifying individuals from different angles, under poor lighting conditions, or when facial features are obscured (e.g., by makeup or accessories).
Potential bias and discrimination: Studies suggest that facial recognition software may exhibit biases, leading to the misidentification of minorities or individuals from underrepresented groups. This could result in unjust questioning, wrongful arrests, or harassment.
Lack of transparency: There are concerns about how the collected facial data is stored, used, and shared, with little public knowledge about data protection policies.

While facial recognition technology offers significant security benefits, its ethical implications cannot be ignored. There is a growing debate on whether stricter regulations or a complete ban on LFR technology is necessary to balance security and privacy.

2. Coronavirus: How can AI help fight the pandemic? (Wakefield, 2020)

The second article, written by Jane Wakefield and published on BBC, explores how Artificial Intelligence (AI) has been instrumental in managing and mitigating the COVID-19 pandemic.

Key Stakeholders

The main stakeholders in this technological application include:

Healthcare professionals – doctors, researchers, and public health officials who utilize AI-driven insights.
Patients and the general public – individuals benefiting from AI-based predictions, diagnostics, and medical advancements.
Technology companies – organizations developing AI-powered healthcare solutions.
Social media platforms – companies like Facebook and YouTube that contribute data and help in public awareness campaigns.

IT System and Area of Application

Technology Used: Artificial Intelligence (Machine Learning, Big Data Analytics, and Robotics).

Application Area: Healthcare and pandemic management.

How AI Helps in Fighting COVID-19

AI plays a crucial role in various aspects of pandemic management, including:

Predicting the spread of the virus: AI algorithms analyze large datasets, including movement patterns from social media and mobile networks, to predict high-risk zones.

Developing vaccines and treatments: AI assists in analyzing biological data, accelerating vaccine research and the development of potential treatments.

Enhancing public awareness: Platforms like YouTube use AI to detect and remove misinformation, while social media sites provide real-time updates on safety guidelines.

AI-powered robots in hospitals: Robots equipped with AI help in sanitization, delivering medical supplies, and even assisting healthcare workers to reduce human exposure to infected individuals.

Positive Social Impacts

Faster detection and containment: AI helps identify outbreak hotspots and enables authorities to take early action.

Medical advancements: AI accelerates drug discovery and vaccine production, reducing research time significantly.

Reduced human exposure: AI-powered robots minimize the risk to healthcare workers, ensuring safer working conditions.

Negative Social and Ethical Concerns

Privacy issues: Large-scale data collection from social media and mobile devices raises concerns about user privacy and potential misuse of personal information.

Risk of misinformation: AI-based algorithms may sometimes misinterpret data, leading to inaccurate predictions or biased decision-making.

Job displacement: Increased reliance on AI automation in hospitals and healthcare facilities may lead to job losses for certain healthcare workers.

AI has proven to be a powerful tool in the fight against COVID-19, enabling early detection, vaccine development, and patient care. However, ethical considerations regarding data privacy and job security must be addressed as AI adoption in healthcare continues to grow.

Conclusion

Both of these case studies highlight the increasing role of IT systems in modern society. While facial recognition enhances security, it raises privacy concerns, and while AI aids healthcare advancements, it poses ethical challenges related to data privacy and automation.

Technology is a double-edged sword, its impact depends on how it is implemented and regulated. As IT continues to evolve, striking a balance between innovation, security, and ethical responsibility remains crucial.

Note: This analysis highlights the impact of IT systems in various sectors, considering both benefits and ethical concerns. If you need a detailed, plagiarism-free solution for a similar task, feel free to contact us!