Unit 5: Ethics, Security, Sustainability & Leadership in Emerging Tech

Emerging technologies like Artificial Intelligence (AI), Cloud Computing, Internet of Things (IoT), and Blockchain are rapidly changing business operations. With these technologies come important responsibilities related to ethics, data privacy, security, sustainability, and leadership.

Ethics in Emerging Technologies

Ethics means doing the right thing while using technology.

Why ethics is needed?

• Technology collects personal data
• Machines take decisions that affect people
• Automation may replace jobs
• AI can be biased if trained on wrong data

Ethical concerns

Area	Explanation in simple terms
Data misuse	Companies using personal data without permission
AI bias	If AI is trained on biased data, it gives unfair results
Job loss	Automation may remove human jobs
Misleading technologies	Deepfakes, fake news, fraud using tech

Example: A bank uses AI for loan approval. If AI is trained on biased data, it may reject applications from certain regions unfairly.

Ethical action: Train AI fairly, keep transparency, review decisions.

Data Privacy, Security & Compliance

• Data Privacy: Protecting personal information of people (name, phone number, address, bank data).
• Data Security: Preventing data theft, hacking, and unauthorized access.
• Compliance: Following rules and laws related to data.

Important Regulations

Regulation	Meaning
GDPR (General Data Protection Regulation – Europe)	Strict law for protecting user data; users must know how their data is used
India: Digital Personal Data Protection Act (DPDP Act)	Indian law for data privacy and digital data security
HIPAA (USA)	Health data privacy
CCPA (California)	Consumer privacy law

Key Principles

• Take permission before collecting data
• Use data only for stated purpose
• Provide option to delete data
• Keep data secure

Cybersecurity in Cloud, AI, IoT & Blockchain

Emerging tech brings new security challenges.

Cloud Security Issues

Issue	Explanation
Data breaches	Hackers may attack online servers
Unauthorized access	Weak passwords or login systems cause risk
Shared responsibility	Cloud provider + company both must secure data

AI Security Issues

Issue	Explanation
Data poisoning	Hackers feed wrong data to AI system
Model theft	AI models can be copied or misused
Algorithm manipulation	Fake input can fool AI (example: fake faces unlocking phones)

IoT Security Issues

Issue	Explanation
Weak devices	Smart devices like CCTV, smart homes can be hacked
Data interception	Network attacks steal device data
Botnets	Hackers control thousands of IoT devices for attacks

Example: Hacking a smart home camera → privacy threat.

⛓ Blockchain Security Issues

Issue	Explanation
51% attack	If one group controls majority of network, they can manipulate data
Smart contract bugs	Errors in blockchain code cause money loss
Crypto wallet hacking	Private keys can be stolen

Sustainability in Technology

Sustainability means using technology in a way that protects the environment and future generations.

Key points

Area	Meaning
Energy-efficient data centers	Reduce electricity use
E-waste management	Recycle old electronic devices
Green AI	Using less power in AI processing
Cloud instead of hardware	Reduce physical machines to save resources

Leadership in Digital Age

Modern leaders must:

Skill	Description
Tech awareness	Understand AI, cloud, automation basics
Ethical vision	Ensure fairness & transparency
Security mindset	Focus on cybersecurity training
Change management	Help employees adapt to new technology
Sustainability focus	Encourage green computing initiatives

Conclusion

Topic	Simple Explanation
Ethics	Use tech responsibly & fairly
Data Privacy	Keep people's personal info safe
Security	Protect systems from hacking
Compliance	Follow legal rules (GDPR, DPDP Act etc.)
Sustainability	Use tech in eco-friendly way
Leadership	Guide people in using new tech responsibly

Ethics and Bias in AI, Big Data, and Immersive Technologies

What is Ethics in Technology?

Ethics means using technology in a fair, honest, and responsible way, without harming people or society.

Ethics & Bias in AI

AI learns from data. If the data has bias, AI gives biased decisions.

Issue	Simple Meaning	Example
AI Bias	AI favors one group unfairly	A hiring AI prefers men over women because the training data had more male candidates
Transparency	Knowing how AI makes decisions	"Black box" AI (decisions unknown)
Accountability	Who is responsible for AI mistakes?	Self-driving car accident — who is guilty?

Solution: Use diverse data, human supervision, ethical guidelines, regular audits.

Ethics & Bias in Big Data

Big data = huge amount of digital information.

Ethical Risk	Explanation
Privacy issues	Tracking user behavior without permission
Data misuse	Selling data to companies without informing users
Surveillance	Using data to spy on people

Solution: user consent, data protection laws, secure storage.

Ethics in Immersive Tech (AR/VR/Metaverse)

Immersive tech creates digital environments.

Issue	Meaning
Misleading reality	Fake environments can manipulate people
Mental health issues	Addiction, social isolation
Data privacy	VR devices track motion, eye movement, voice
Harassment	Cyberbullying in virtual world

Solution: user safety policies, age filters, controlled environments.

Sustainable Technology Adoption & Digital Responsibility

Sustainable Technology Adoption

Using technology in a way that is environment-friendly, cost-efficient, and future-ready.

Concept	Meaning
Green Data Centers	Low-power servers & cooling systems
Energy-efficient AI	Optimized algorithms that use less power
E-waste reduction	Recycling old devices
Cloud computing	Reduce physical machines to save energy
Green supply chain tech	Use digital tools to reduce waste & emissions

Digital Responsibility

Using digital tools safely, ethically, and responsibly.

Area	Meaning
Online behavior	No bullying, trolling, fake news
Data protection	Strong passwords, privacy settings
Cyber awareness	Avoid phishing, scams, malware
Digital wellness	Limit screen time, avoid addiction

Leadership & Future Workplace Skills

Technology is changing jobs. Future leaders must learn new skills to manage innovation and digital teams.

Managing Innovation

Innovation means introducing new ideas, products, or processes.

Skill	Meaning
Creative thinking	Encourage fresh ideas
Tech adoption	Use AI, Cloud, Automation in business
Risk taking	Try new solutions
Cross-functional collaboration	Work with IT, marketing, finance, HR teams

Change Management

Helping employees adapt to new technology and processes.

Step	Simple Meaning
Communicate change	Explain why change is needed
Train employees	Workshops, demos, learning
Remove fear & resistance	Motivate employees, reduce job insecurity
Continuous support	Provide help & feedback

Digital Strategy

Planning how a company uses digital tools to achieve goals.

Component	Meaning
Digital vision	Where company wants to go using technology
Tech investments	Choosing right tools (AI, CRM, ERP, Cloud)
Data-driven decisions	Use analytics instead of guesswork
Cybersecurity planning	Protect business data
Customer experience	Improve service using technology

Future Workplace Skills

Skill	Why Important
Digital literacy	Understand tech basics (AI, Cloud, CRM)
Analytical thinking	Make decisions using data
Emotional intelligence	Manage people, empathy in digital workplace
Agility & adaptability	Quickly adjust to new technologies
Team collaboration	Work with remote & digital teams
Ethical mindset	Fair and responsible leadership

Conclusion

Topic	Key Idea
Ethics & Bias	Ensure fairness & transparency in AI and tech
Sustainable Tech	Use eco-friendly & responsible digital solutions
Leadership Skills	Adapt to tech, manage innovation & change