The document outlines some of the ethical issues arising from emerging technologies such as artificial intelligence, big data, and the internet of things. It discusses how technologies can both promote and restrict human rights, and how legal and regulatory frameworks have struggled to keep pace with digital transformation. Some specific challenges mentioned include potential discrimination from algorithmic decision-making, loss of jobs to automation, and new privacy and security risks from mass connectivity and data collection. The document stresses the importance of considering ethics early in technology development to help ensure technologies are developed and applied responsibly and for the benefit of all.
Ethics and Responsible AI Deployment
Abstract: As Artificial Intelligence (AI) becomes more prevalent, protecting personal privacy is a critical ethical issue that must be addressed. This article explores the need for ethical AI systems that safeguard individual privacy while complying with ethical standards. By taking a multidisciplinary approach, the research examines innovative algorithmic techniques such as differential privacy, homomorphic encryption, federated learning, international regulatory frameworks, and ethical guidelines. The study concludes that these algorithms effectively enhance privacy protection while balancing the utility of AI with the need to protect personal data. The article emphasises the importance of a comprehensive approach that combines technological innovation with ethical and regulatory strategies to harness the power of AI in a way that respects and protects individual privacy.
Artificial intelligence (AI) has the potential to significantly impact employment, social equity, and economic systems in ways that require careful ethical analysis and aggressive legislative measures to mitigate negative consequences. This means that the implications of AI in different industries, such as healthcare, finance, and transportation, must be carefully considered.
Due to the global nature of AI technology, global collaboration must be fostered to establish standards and regulatory frameworks that transcend national boundaries. This includes the establishment of ethical guidelines that AI researchers and developers worldwide should follow.
To address emergent ethical concerns with AI, future research must focus on several recommendations. Firstly, ethical considerations must be integrated into the design phase of AI systems and not treated as an afterthought. This is known as "Ethics by Design" and involves incorporating ethical standards during the development phase of AI systems to ensure that the technology aligns with ethical principles.
Secondly, interdisciplinary research that combines AI, ethics, law, social science, and other relevant domains should be promoted to produce well-rounded solutions to ethical dilemmas. This requires the participation of experts from different fields to identify and address ethical issues.
Thirdly, regulatory frameworks must be dynamic and adaptive to keep pace with the rapid evolution of AI technologies. This means that regulatory frameworks must be flexible enough to accommodate changes in AI technology while ensuring ethical standards are maintained.
Fourthly, empirical research should be conducted to understand the real-world implications of AI systems on individuals and society, which can then inform ethical principles and policies. This means that empirical data must be collected to understand how AI affects people in different contexts.
Finally, risk assessment procedures should be improved to better analyse the ethical hazards associated with AI applications.
Briefly describe the research design
Who the target population
Was the sampling method and the sample size appropriate? Why?
Any selection bias in sampling and representativeness?
Does the article you selected have a model specification? If yes, is the specified model congruent with the conceptual framework? If no, what went wrong?
What method of data analysis did the author(s) use? Is it appropriate
The presentation is all about the issues in professional ethics. This talks about the failures of ethics in Information Technology. Sliding thru the powerpoint gives you a hint what are the ethical and social issues in information systems
Ethics of Computing in Pharmaceutical ResearchAshwani Dhingra
Computing ethics is a set of moral principles that regulate the use of computers. In pharmaceutical research computers, computing technology, and consequent information system has produced ethical challenges and conflicts.
Ethics and Responsible AI Deployment
Abstract: As Artificial Intelligence (AI) becomes more prevalent, protecting personal privacy is a critical ethical issue that must be addressed. This article explores the need for ethical AI systems that safeguard individual privacy while complying with ethical standards. By taking a multidisciplinary approach, the research examines innovative algorithmic techniques such as differential privacy, homomorphic encryption, federated learning, international regulatory frameworks, and ethical guidelines. The study concludes that these algorithms effectively enhance privacy protection while balancing the utility of AI with the need to protect personal data. The article emphasises the importance of a comprehensive approach that combines technological innovation with ethical and regulatory strategies to harness the power of AI in a way that respects and protects individual privacy.
Artificial intelligence (AI) has the potential to significantly impact employment, social equity, and economic systems in ways that require careful ethical analysis and aggressive legislative measures to mitigate negative consequences. This means that the implications of AI in different industries, such as healthcare, finance, and transportation, must be carefully considered.
Due to the global nature of AI technology, global collaboration must be fostered to establish standards and regulatory frameworks that transcend national boundaries. This includes the establishment of ethical guidelines that AI researchers and developers worldwide should follow.
To address emergent ethical concerns with AI, future research must focus on several recommendations. Firstly, ethical considerations must be integrated into the design phase of AI systems and not treated as an afterthought. This is known as "Ethics by Design" and involves incorporating ethical standards during the development phase of AI systems to ensure that the technology aligns with ethical principles.
Secondly, interdisciplinary research that combines AI, ethics, law, social science, and other relevant domains should be promoted to produce well-rounded solutions to ethical dilemmas. This requires the participation of experts from different fields to identify and address ethical issues.
Thirdly, regulatory frameworks must be dynamic and adaptive to keep pace with the rapid evolution of AI technologies. This means that regulatory frameworks must be flexible enough to accommodate changes in AI technology while ensuring ethical standards are maintained.
Fourthly, empirical research should be conducted to understand the real-world implications of AI systems on individuals and society, which can then inform ethical principles and policies. This means that empirical data must be collected to understand how AI affects people in different contexts.
Finally, risk assessment procedures should be improved to better analyse the ethical hazards associated with AI applications.
Briefly describe the research design
Who the target population
Was the sampling method and the sample size appropriate? Why?
Any selection bias in sampling and representativeness?
Does the article you selected have a model specification? If yes, is the specified model congruent with the conceptual framework? If no, what went wrong?
What method of data analysis did the author(s) use? Is it appropriate
The presentation is all about the issues in professional ethics. This talks about the failures of ethics in Information Technology. Sliding thru the powerpoint gives you a hint what are the ethical and social issues in information systems
Ethics of Computing in Pharmaceutical ResearchAshwani Dhingra
Computing ethics is a set of moral principles that regulate the use of computers. In pharmaceutical research computers, computing technology, and consequent information system has produced ethical challenges and conflicts.
Ethical Considerations in Data Analysis_ Balancing Power, Privacy, and Respon...Soumodeep Nanee Kundu
The explosion of data and the increasing capabilities of data analysis have transformed various aspects of our lives. From healthcare and finance to marketing and law enforcement, data analysis has become an essential tool for decision-making and problem-solving. However, with great power comes great responsibility. Ethical considerations in data analysis are more critical than ever as data professionals grapple with questions related to privacy, fairness, transparency, and accountability. In this article, we will delve into the ethical challenges that data analysts and organizations face and explore strategies to address them.
Module 2: Cyber-Crimes and Cyber Laws
Ethics for IT Workers and IT Users-IT Professionals-IT professional malpractice-IT , IT Act cyber
laws - Information Technology Act, 2000 (“IT Act”) - Digital Signature - Confidentiality, Integrity and Authenticity (CIA)
e-SIDES workshop at BDV Meet-Up, Sofia 14/05/2018e-SIDES.eu
The following presentation was given at the workshop "Technology solutions for privacy issues: what is the best way forward?" organized by e-SIDES at the BDVe Meet-up in Sofia on May 14, 2018. The workshop, chaired by Gabriella Cattaneo from IDC, involved stakeholders from ICT-18 projects.
Delivered at Trend Micro's Executive briefing events Sydney and Melbourne 5-6 June 2017 on Australia's new Mandatory Data Breach Notification legislation. YoutubeVideo available at https://youtu.be/j5nmY916H7k
Article started one year ago, obtains far more relevancy these days. Its meaning stays the same however: "Without laws and regulations would be chaos affecting our freedom and human nature."
Ethical Considerations in Data Analysis_ Balancing Power, Privacy, and Respon...Soumodeep Nanee Kundu
The explosion of data and the increasing capabilities of data analysis have transformed various aspects of our lives. From healthcare and finance to marketing and law enforcement, data analysis has become an essential tool for decision-making and problem-solving. However, with great power comes great responsibility. Ethical considerations in data analysis are more critical than ever as data professionals grapple with questions related to privacy, fairness, transparency, and accountability. In this article, we will delve into the ethical challenges that data analysts and organizations face and explore strategies to address them.
Module 2: Cyber-Crimes and Cyber Laws
Ethics for IT Workers and IT Users-IT Professionals-IT professional malpractice-IT , IT Act cyber
laws - Information Technology Act, 2000 (“IT Act”) - Digital Signature - Confidentiality, Integrity and Authenticity (CIA)
e-SIDES workshop at BDV Meet-Up, Sofia 14/05/2018e-SIDES.eu
The following presentation was given at the workshop "Technology solutions for privacy issues: what is the best way forward?" organized by e-SIDES at the BDVe Meet-up in Sofia on May 14, 2018. The workshop, chaired by Gabriella Cattaneo from IDC, involved stakeholders from ICT-18 projects.
Delivered at Trend Micro's Executive briefing events Sydney and Melbourne 5-6 June 2017 on Australia's new Mandatory Data Breach Notification legislation. YoutubeVideo available at https://youtu.be/j5nmY916H7k
Article started one year ago, obtains far more relevancy these days. Its meaning stays the same however: "Without laws and regulations would be chaos affecting our freedom and human nature."
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
2. Technology and
ethics
• The Internet boom has provided many benefits for society,
allowing the creation of new tools and new ways for people
to interact.
• As with many technological advances, however, the Internet
has not been without negative aspects.
• For example, it has created new concerns about privacy,
and it has been hampered by spam and viruses.
• Moreover, even as it serves as a medium for communication
across the globe, it threatens to cut off people who lack
access to it.
2
3. Ø Technology can serve to promote or restrict human rights.
Ø The Information Society should foster the use of emerging technologies in
such a way as to maximize the benefits that they provide while minimizing
the harms.
Ø In many cases, this promotion may be less a matter of technological control
than of oversight: establishing the proper legal or regulatory system to
ensure that technology capable of abuse is not in fact abused and that the
benefits of technology are shared among all.
Technology and
ethics
3
4. Ethics is particularly important for the accountancy profession,
with a code for professional ethics based on five basic
principles – integrity, objectivity, competence and due care,
confidentiality, and professional behavior.
However, the emergence of new technologies raises some new
challenges for the profession to address.
Technology and
ethics
4
5. The increasing use of big data, algorithmic decision-making,
and artificial intelligence can enable more consistent, evidence-
based and accurate judgments or decisions, often more quickly
and efficiently.
However, these strengths can potentially have a darker side too,
throwing up questions around the ethical use of these fairly new
technologies.
For example, outputs can be based on biased data, which could
lead to discriminatory outcomes.
New ethical
questions
5
6. Indeed, where systems learn from real-world data, there is a
significant risk that those systems simply recreate the past and
subsequently build in errors or systemic biases.
Closely linked to discrimination is personalization, and the
impact of tailoring decisions very specifically to individuals,
based on preferences, activities and other features.
While this can be beneficial for many, others can lose out, and
outcomes can again seem unfair or unethical.
New ethical
questions
6
7. • Additionally, questions are being asked regarding the interaction
between computers and humans.
• How much reliance can we place on data and models, and what
is the role of human judgment, as well as how do we ensure
that we understand the decision-making process?
• Whatever the power of the machine, humans will still need to be
involved, so that people can be held accountable, or explain the
reasons behind a decision.
•
New ethical
questions
7
8. • A central problem of the ethics of technology is that it tends
to arrive too late. In many cases, ethical issues are only recognized
when the technology is already on the market and problems arise
during its widespread use.
• Ethics can then become a tool to clean up a mess that might have
been avoidable.
• It is probably not contentious to say it would be desirable to have
ethical input at the earlier stages of technology design and
development.
New ethical
questions
8
9. Indeed, there are ethical theories and approaches that explicitly aim at an early
integration of ethics into the technology life cycle.
One central problem of this type of approach is that the future is unknown.
We do not know with certainty what will happen in the future and ethics that
relies on future development needs to be able to answer the question of how it
decides which technological developments to pursue.
Ethics has traditionally not been well equipped to deal with issues of uncertainty
and future uncertainty.
New ethical
questions
9
10. Ethical rules
• Contribute to society and to human well-being, acknowledging that
all people are stakeholders in computing.
• Avoid harm.
• Be honest and trustworthy.
• Be fair and act not to discriminate
• Respect the work required to produce new ideas, inventions, creative
works, and computing artifacts.
• Respect privacy.
• Honor confidentiality
General ethical
principles
10
11. Professional responsibilities.
• Strive to achieve high quality in both the processes and
products of professional work.
• Maintain high standards of professional competence, conduct,
and ethical practice.
• Know and respect existing rules pertaining to professional
work.
• Accept and provide appropriate professional review.
General ethical
principles
11
12. • Give comprehensive and thorough evaluations of computer
systems and their impacts, including analysis of possible risks.
• Perform work only in areas of competence.
• Foster public awareness and understanding of computing,
related technologies, and their consequences.
• Access computing and communication resources only when
authorized or when compelled by the public good.
• Design and implement systems that are robustly and usably
secure.
Professional responsibilities.
General ethical
principles
12
13. Professional leadership principles.
• Ensure that the public good is the central concern during all
professional computing work.
• Articulate, encourage acceptance and evaluate fulfillment of
social responsibilities by members of the organization or group.
• Manage personnel and resources to enhance the quality of
working life.
• Articulate, apply, and support policies and processes that reflect
the principles of the Code.
General ethical
principles
13
14. • Create opportunities for members of the organization or group
to grow as professionals.
• Use care when modifying or retiring systems.
• Interface changes, the removal of features, and even software
updates have an impact on the productivity of users and the
quality of their work.
• Recognize and take special care of systems that become
integrated into the infrastructure of society.
Professional leadership principles
General ethical
principles
14
15. • Digital Privacy is the protection of personally identifiable
or business identifiable information that is collected from
respondents through information collection activities or
from other sources
• It Contains:
• Information privacy,
• communication privacy, and
• Individual privacy
Digital privacy
General ethical
principles
15
16. • Data Minimization: collect the minimal amount of information
necessary from individuals and businesses consistent with the
Department’s mission and legal requirements.
• Transparency: Notice covering the purpose of the collection and
use of identifiable information will be provided in a clear
manner.
• Information collected will not be used for any other purpose
unless authorized or mandated by law.
Digital privacy
Some digital
privacy
principles
16
17. • Accuracy: Information collected will be maintained in a
sufficiently accurate, timely, and complete manner to ensure that
the interests of the individuals and businesses are protected.
• Security: Adequate physical and IT security measures will be
implemented to ensure that the collection, use, and maintenance
of identifiable information are properly safe guarded.
• Information is promptly destroyed in accordance with approved
records control schedules.
Digital privacy
Some digital
privacy
principles
17
18. • When emerging technology creates far-reaching and rapid change,
it can also bring new risks.
• Understanding and mitigating them will help to build confidence.
• Often legal and regulatory frameworks haven’t kept pace with
digital transformation, and organizations are seeking guidance.
• This challenge is exacerbated by the speed at which technological
change is occurring and the breadth of its adoption – which is
introducing new risks that demand new responses.
Accountability
and
Trust
18
19. • Emerging technologies can provide improved accuracy, better
quality and cost efficiencies for businesses in every sector.
They can enhance trust in the organization’s operations and
financial processes, which is crucial for sustainable success.
• But this can produce a paradox: the very solutions that can be
used to better manage risk, increase transparency and build
confidence are often themselves the source of new risks, which
may go unnoticed.
Accountability
and Trust
19
20. • There’s a danger that the use of technology will degrade people’s
willingness to judge and intervene because they feel that they are less
personally connected to consumers and consumer outcomes – the logic
of the machine has taken over from individual responsibility.
• The obligation of an individual or organization to account for its
activities, accept responsibility for them, and to disclose the results in a
transparent manner.
• It also includes the responsibility for money or other entrusted
property.
Accountability
and Trust
20
21. Ethical and regulatory challenges
• With Technology moving at a fast pace it is always been a challenge for
Security.
• As security professionals, we need to keep pace with ever-changing
technology and be aware of the AI, IoT, Big Data, Machine Learning, etc.
• Emerging technologies are making an impact include:
• Counter-terrorism and law enforcement informatics via predictive
analytics and artificial intelligence.
• Real-time horizon scanning and data mining for threats and information
sharing
• Automated cybersecurity and information assurance
Treats and
challenges
21
22. • Enhanced Surveillance (chemical and bio-detection sensors, cameras,
drones, facial recognition, license plate readers)
• Simulation and augmented reality technologies for training and
modeling
• Safety and security equipment (including bullet and bomb proof) made
with lighter and stronger materials
• Advanced forensics enabled by enhanced computing capabilities
(including future quantum computing)
• Situational awareness capabilities via GPS for disaster response and
crisis response scenarios
Treats and
challenges
Con…
22
23. • Biometrics: assured identity security screening solutions by bio-
signature: (every aspect of your physiology can be used as a bio-
signature. Measure unique heart/pulse rates, electrocardiogram
sensor, blood oximetry, skin temperature)
• Robotic Policing (already happening in Dubai!)
Treats and
challenges
Con…
23
24. • With automation and robotics moving from production lines out
into other areas of work and business, the potential for humans
losing jobs is great here too.
• As automation technologies become more advanced, there will
be a greater capability for automation to take over more and
more complex jobs.
• As robots learn to teach each other and themselves, there is the
potential for much greater productivity, but this also raises
ethical and cybersecurity concerns.
Treats and
challenges
Challenges in using Artificial Intelligence
24
25. • As more and more connected devices (such as smartwatches and
fitness trackers) join the Internet of Things (IoT) the amount of
data being generated is increasing.
• Companies will have to plan carefully how this will affect the
customer-facing application and how to best utilize the masses of
data being produced.
• There are also severe security implications of mass connectivity
that need to be addressed.
Treats and
challenges
Challenges in using the Internet of Things
25
26. Almost all the technologies mentioned above have some relation
to Big Data.
The huge amount of data being generated daily has the potential
to provide businesses with better insight into their customers as
well as their own business operations.
Although data can be incredibly useful for spotting trends and
analyzing impacts, surfacing all this data to humans in a way that
they can understand can be challenging. AI will play a role here.
Treats and
challenges
Challenges in Big Data
26
27. • Some risks of emerging technology are:
• Driverless car: while a compelling option for future fleer cars,
companies could crash and burn from claims related to bodily
injury and property damage.
• Wearables: Google glass, Fitbit and other wearables can expose
companies to the invasion of privacy claims that may not be
covered by general liability or personal injury claims that weren’t
foreseen.
Treats and
challenges
Treats
27
28. Some risks of emerging technology are:
Drones: Turbulence is in the offing for manufacturers and
organizations that fail to protect themselves for property damage
and bodily injury, as well as errors and omissions.
Internet of things: The proliferation of sensors and cross-platform
integration creates potential exposure from privacy invasion, bodily
injury and property damage that may connect an organization to
huge liabilities.
Treats and
challenges
Treats
28
29. References
“Think before you speak. Read before you think.” – Fran Lebowitz
“Ethics and new technologies.” [Online]. Available: https://www.icaew.com/technical/ethics/ethics-and-
new-technologies. [Accessed: 25-Aug-2019].
J. Weckert and R. Lucas, Professionalism in the Information and Communication Technology Industry.
Canberra: ANU Press, 2013.
“Code of Ethics,” PROFESSIONAL CERTIFICATIONS FOR EMERGING TECH. [Online]. Available:
http://iccp.org/code-of-ethics.html. [Accessed: 25-Aug-2019].
“IT Privacy Policy, Office of Privacy and Open Government, U.S. Department of Commerce.” [Online].
Available: http://www.osec.doc.gov/opog/privacy/digital_policy.html. [Accessed: 25- Aug-2019].143
29
30. References
“As technology advances, will accountability be a casualty?” [Online]. Available:
https://www.ey.com/en_gl/banking-capital-markets/as-technology-advances-will-accountabilitybe-a-
casualty. [Accessed: 02-Sep-2019].
“How can you build trust when emerging technologies bring new risks?” [Online]. Available:
https://www.ey.com/en_gl/digital/how-can-you-build-trust-when-emerging-technologies-bringnew-
risks. [Accessed: 02-Sep-2019].
“What comes after those ellipses?,” BusinessDictionary.com. [Online]. Available:
http://www.businessdictionary.com/definition/accountability.html. [Accessed: 08-Sep-2019].
30
31. References
“‘Emerging Technologies are Already Impacting Security Strategies,’” IFSEC India, 11-Jan-2019.
[Online]. Available: https://www.ifsec.events/india/visit/news-and-updates/emergingtechnologies-are-
already-impacting-security-strategies. [Accessed: 02-Sep-2019].
C. Lovatt, “5 Big Technology Challenges For Enterprises In The Future.” [Online]. Available:
https://blog.cutover.com/technology-challenges-enterprises-future. [Accessed: 08-Sep-2019].
“What are the ethical implications of emerging tech?,” World Economic Forum. [Online]. Available:
https://www.weforum.org/agenda/2015/03/what-are-the-ethical-implications-ofemerging-tech/.
[Accessed: 25-Aug-2019].
B. Dainow, “Ethics in Emerging Technology,” ITNOW, vol. 56, pp. 16–18, Aug. 2014.
“7 Emerging Technology Risks,” Risk & Insurance, 04-Aug-2014. [Online]. Available:
https://riskandinsurance.com/7-emerging-tech-risks/. [Accessed: 08-Sep-2019].
“12 Examples of Artificial Intelligence: AI Powers Business.” [Online]. Available:
https://www.datamation.com/artificial-intelligence/examples-of-artificial-intelligence.html. [Accessed:
09-Nov-2019].
31