This course was about business ethics... here we discuss about ethics of technology that what are the ethics used for implementing technology... I learned it from Institute of Business Management IoBM...
This course was about business ethics... here we discuss about ethics of technology that what are the ethics used for implementing technology... I learned it from Institute of Business Management IoBM...
Ethics in Data Science and Machine LearningHJ van Veen
Introduction and overview on ethics in data science and machine learning, variations and examples of algorithmic bias, and a call-to-action for self-regulation. Given by Thierry Silbermann as part of the Sao Paulo Machine Learning Meetup, theme: "Ethics".
https://www.linkedin.com/in/thierrysilbermann
https://twitter.com/silbermannt
https://github.com/thierry-silbermann
An Introduction: Technology, Ethics, and the WorkplaceTawny Brown
Learning Objectives:
1. Explore ethical questions resulting from increased use of technology in the workplace.
2. Understand benefits and challenges created by use of technology in the workplace.
3. Discuss the potential impact of personal use of technology on professional life.
4. Explore strategies for addressing potential ethical concerns in using technology.
Computer Ethics: Ethics is a set of moral principles that govern the behavior of a group or individual. Therefore, computer ethics is set of moral principles that regulate the use of computers. Some common issues of computer ethics include intellectual property rights (such as copyrighted electronic content), privacy concerns, and how ...
Ethics in Data Science and Machine LearningHJ van Veen
Introduction and overview on ethics in data science and machine learning, variations and examples of algorithmic bias, and a call-to-action for self-regulation. Given by Thierry Silbermann as part of the Sao Paulo Machine Learning Meetup, theme: "Ethics".
https://www.linkedin.com/in/thierrysilbermann
https://twitter.com/silbermannt
https://github.com/thierry-silbermann
An Introduction: Technology, Ethics, and the WorkplaceTawny Brown
Learning Objectives:
1. Explore ethical questions resulting from increased use of technology in the workplace.
2. Understand benefits and challenges created by use of technology in the workplace.
3. Discuss the potential impact of personal use of technology on professional life.
4. Explore strategies for addressing potential ethical concerns in using technology.
Computer Ethics: Ethics is a set of moral principles that govern the behavior of a group or individual. Therefore, computer ethics is set of moral principles that regulate the use of computers. Some common issues of computer ethics include intellectual property rights (such as copyrighted electronic content), privacy concerns, and how ...
Dr Masood Ahmed and Alan Davies - ECO 17: Transforming care through digital h...Innovation Agency
Presentation by Dr Masood Ahmed, Advisor, Digital Health London and Alan Davies, Director of Digital Health, Innovation Agency: Getting AI into practice in the NHS at ECO 17: Transforming care through digital health on Tuesday 4 December at Lancaster University, Lancaster
AI Governance and Ethics - Industry StandardsAnsgar Koene
Presentation on the potential for Ethics based Industry Standards to function as vehicle to address socio-technical challenges from AI.
Presentation given at the the 1st Austrian IFIP forum ono "AI and future society".
Cyber Ethics An Introduction by Paul A. Adekunte | Matthew N. O. Sadiku | Jan...ijtsrd
Cyber ethics is the study of the ethics relating to computers, as well as to user behavior and what computers are programmed to do, and how it affects individuals and society. It is the branch of philosophy that deals with what is considered to be right or wrong. Since the advent of computers, various governments have enacted regulations and while organizations have defined policies about cyberethics. Cyberethics also known as “internet ethics,” is a branch of applied ethics that examines the moral, legal, and social issues i.e. ethical questions brought about by the emergence of digital technologies and global virtual environments. Arising with the introduction of the internet are, filtering, accuracy, security, censorship, conflicts over privacy, property, accessibility, and others. This paper is to elucidate more on cyberethics and its impacts on users and the society Paul A. Adekunte | Matthew N. O. Sadiku | Janet O. Sadiku "Cyber Ethics: An Introduction" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd63513.pdf Paper Url: https://www.ijtsrd.com/computer-science/computer-security/63513/cyber-ethics-an-introduction/paul-a-adekunte
Data; Data manipulation, sorting, grouping, rearranging. Plotting the data. D...jybufgofasfbkpoovh
Data; Data manipulation, sorting, grouping, rearranging. Plotting the data. Descriptive statistics. Inferential statistics. Python Libraries for Data Science.
Shaping Ethics in the Digital Age - Connected and Open Research Ethics (CORE)Gayle Simon
@CamilleNebeker, Ed.D., M.S., gave the keynote address at an OHRP sponsored RCF in Hartford, Connecticut, speaking about the ethical use of personal health data and data from mobile technologies in research. Dr. Nebeker is an Assistant Professor of Behavioral Medicine, Family Medicine, and Public Health in the UC San Diego School of Medicine.
Ethics in Library Research Data Services: Conceptual Gaps & Policy VacuumsMichael Zimmer
Prepared for the ALISE Webinar on "Ethics in Library Research Data Services," this presentation discusses some of the conceptual gaps and policy vacuums that emerge alongside the rise of big data-based research, and how these pose challenges for us as ethicists and as library practitioners
Thinking about Open Science practices, data sharing and lifetime, and communication from Climate Scientists. Slides based on a presentation given at the Lunchtime talk sessions from the MetOS Section, Department of Geosciences, University of Oslo, November 12th 2015.
Ethical Priniciples for the All Data RevolutionMelissa Moody
A presentation by Stephanie Shipp, from the Research Highlights session at the 2019 Women in Data Science Charlottesville Conference. Hosted by the UVA Data Science Institute.
An introductory take on the ethical issues surrounding the use of algorithms and machine learning in finance, education, law enforcement and defense. This work was stimulated by, but is not a product or authorized content from the IEEE P7003 WG.
Disclaimer: This work is mine alone and does not reflect view of IEEE, IEEE 7003 WG, my employer.
How to get started on your data governance journey and support your cyber and information security programs. Presented at the AISA Cyber Conference Canberra March 2021
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
Climate Impact of Software Testing at Nordic Testing DaysKari Kakkonen
My slides at Nordic Testing Days 6.6.2024
Climate impact / sustainability of software testing discussed on the talk. ICT and testing must carry their part of global responsibility to help with the climat warming. We can minimize the carbon footprint but we can also have a carbon handprint, a positive impact on the climate. Quality characteristics can be added with sustainability, and then measured continuously. Test environments can be used less, and in smaller scale and on demand. Test techniques can be used in optimizing or minimizing number of tests. Test automation can be used to speed up testing.
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
GridMate - End to end testing is a critical piece to ensure quality and avoid...ThomasParaiso2
End to end testing is a critical piece to ensure quality and avoid regressions. In this session, we share our journey building an E2E testing pipeline for GridMate components (LWC and Aura) using Cypress, JSForce, FakerJS…
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.
In his public lecture, Christian Timmerer provides insights into the fascinating history of video streaming, starting from its humble beginnings before YouTube to the groundbreaking technologies that now dominate platforms like Netflix and ORF ON. Timmerer also presents provocative contributions of his own that have significantly influenced the industry. He concludes by looking at future challenges and invites the audience to join in a discussion.
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
Removing Uninteresting Bytes in Software FuzzingAftab Hussain
Imagine a world where software fuzzing, the process of mutating bytes in test seeds to uncover hidden and erroneous program behaviors, becomes faster and more effective. A lot depends on the initial seeds, which can significantly dictate the trajectory of a fuzzing campaign, particularly in terms of how long it takes to uncover interesting behaviour in your code. We introduce DIAR, a technique designed to speedup fuzzing campaigns by pinpointing and eliminating those uninteresting bytes in the seeds. Picture this: instead of wasting valuable resources on meaningless mutations in large, bloated seeds, DIAR removes the unnecessary bytes, streamlining the entire process.
In this work, we equipped AFL, a popular fuzzer, with DIAR and examined two critical Linux libraries -- Libxml's xmllint, a tool for parsing xml documents, and Binutil's readelf, an essential debugging and security analysis command-line tool used to display detailed information about ELF (Executable and Linkable Format). Our preliminary results show that AFL+DIAR does not only discover new paths more quickly but also achieves higher coverage overall. This work thus showcases how starting with lean and optimized seeds can lead to faster, more comprehensive fuzzing campaigns -- and DIAR helps you find such seeds.
- These are slides of the talk given at IEEE International Conference on Software Testing Verification and Validation Workshop, ICSTW 2022.
GraphSummit Singapore | The Future of Agility: Supercharging Digital Transfor...Neo4j
Leonard Jayamohan, Partner & Generative AI Lead, Deloitte
This keynote will reveal how Deloitte leverages Neo4j’s graph power for groundbreaking digital twin solutions, achieving a staggering 100x performance boost. Discover the essential role knowledge graphs play in successful generative AI implementations. Plus, get an exclusive look at an innovative Neo4j + Generative AI solution Deloitte is developing in-house.
Sudheer Mechineni, Head of Application Frameworks, Standard Chartered Bank
Discover how Standard Chartered Bank harnessed the power of Neo4j to transform complex data access challenges into a dynamic, scalable graph database solution. This keynote will cover their journey from initial adoption to deploying a fully automated, enterprise-grade causal cluster, highlighting key strategies for modelling organisational changes and ensuring robust disaster recovery. Learn how these innovations have not only enhanced Standard Chartered Bank’s data infrastructure but also positioned them as pioneers in the banking sector’s adoption of graph technology.
Pushing the limits of ePRTC: 100ns holdover for 100 daysAdtran
At WSTS 2024, Alon Stern explored the topic of parametric holdover and explained how recent research findings can be implemented in real-world PNT networks to achieve 100 nanoseconds of accuracy for up to 100 days.
How to Get CNIC Information System with Paksim Ga.pptxdanishmna97
Pakdata Cf is a groundbreaking system designed to streamline and facilitate access to CNIC information. This innovative platform leverages advanced technology to provide users with efficient and secure access to their CNIC details.
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.
Dr. Sean Tan, Head of Data Science, Changi Airport Group
Discover how Changi Airport Group (CAG) leverages graph technologies and generative AI to revolutionize their search capabilities. This session delves into the unique search needs of CAG’s diverse passengers and customers, showcasing how graph data structures enhance the accuracy and relevance of AI-generated search results, mitigating the risk of “hallucinations” and improving the overall customer journey.
1. Data & Digital Ethics: some
thoughts
Kate Carruthers
Version 1.0
August 2017
Classification: PUBLIC
2. Ethics
Moral principles that govern a person's behaviour or the
way in which they conduct an activity…
August 17 Kate Carruthers | UNSW 1
“We ask ethical questions whenever we think
about how we should act. Being ethical is a
part of what defines us as human beings.”
The Ethics Centre, Sydney
4. Digital Ethics?
“A few guidelines are useful in most situations:
• Use the golden rule: ask yourself how you would like to be treated
as a human being, citizen or customer.
• There are always unintended consequences: embrace new positive
uses of technology, and block undesirable uses.
• Success usually comes from exercising discipline and self-restraint
in using technology, rather than pushing the limits.”
August 17 Kate Carruthers | UNSW 3
Goasduff, C. L. (2016, March 07). Kick-Start the Conversation on Digital Ethics. Retrieved August 15, 2017, from
http://www.gartner.com/smarterwithgartner/kick-start-the-conversation-on-digital-ethics/
5. Areas of focus
• Ethics of data - how we generate, record & share
data
• Ethics of algorithms - how we interpret data via
artificial intelligence, machine learning and robots
• Ethics of practices - devising responsible
innovation and professional codes to guide this
emerging science
August 17 Kate Carruthers | UNSW 4
What is data ethics?
Luciano Floridi, Mariarosaria Taddeo
Phil. Trans. R. Soc. A 2016 374
20160360; DOI: 10.1098/rsta.2016.0360. Published
14 November 2016
6. 5 Propositions about data
1.Data is not neutral
2.There is no such thing as raw data
3.The signal to noise ratio has changed
4.Data is not inherently smart
5.The more data we have the less anonymity
August 17 Kate Carruthers | UNSW 5
8. Some food for thought
August 17 7Kate Carruthers | UNSW
9. August 17 Kate Carruthers | UNSW 8
http://www.informationisbeautiful.net/visualizations/worlds-biggest-data-breaches-
hacks/
10. August 17 Kate Carruthers | UNSW 9
This Photo by Unknown Author is licensed under CC BY-NC-SA
11. Facebook study
“We show, via a massive (N = 689,003) experiment on Facebook,
that emotional states can be transferred to others via emotional
contagion, leading people to experience the same emotions without
their awareness. We provide experimental evidence that emotional
contagion occurs without direct interaction between people
(exposure to a friend expressing an emotion is sufficient), and in the
complete absence of nonverbal cues.”
August 17 Kate Carruthers | UNSW 10
Kramer, A. D., Guillory, J. E., & Hancock, J. T. (2014). Experimental evidence of
massive-scale emotional contagion through social networks. Proceedings
of the National Academy of Sciences, 111(24), 8788-8790.
12. August 17 Kate Carruthers | UNSW 11
http://thehackernews.com/2017/07/sweden-data-breach.html
18. 1. Minimize attack surface area
2. Establish secure defaults
3. Principle of Least privilege
4. Principle of Defence in depth
5. Fail securely
6. Don’t trust services
7. Separation of duties
8. Avoid security by obscurity
9. Keep security simple
10. Fix security issues correctly
OWASP Security by Design Principles
August 17 Kate Carruthers | UNSW 17
Open Web Application Security Project
https://www.owasp.org/index.php/Security_by_Design_Principles
19. IEEE CS/ACM Code of Ethics & Professional Practice
Software engineers shall commit themselves to making the analysis, specification, design, development, testing and maintenance of software a
beneficial and respected profession. In accordance with their commitment to the health, safety and welfare of the public, software engineers
shall adhere to the following Eight Principles:
1. Public: Software engineers shall act consistently with the public interest.
2. Client and Employer: Software engineers shall act in a manner that is in the best interests of their client and employer, consistent with the
public interest.
3. Product: Software engineers shall ensure that their products and related modifications meet the highest professional standards possible.
4. Judgement: Software engineers shall maintain integrity and independence in their professional judgment.
5. Management: Software engineering managers and leaders shall subscribe to and promote an ethical approach to the management of
software development and maintenance.
6. Profession: Software engineers shall advance the integrity and reputation of the profession consistent with the public interest.
7. Colleagues: Software engineers shall be fair to and supportive of their colleagues.
8. Self: Software engineers shall participate in lifelong learning regarding the practice of their profession and shall promote an ethical
approach to the practice of the profession.
August 17 Kate Carruthers | UNSW 18
https://www.computer.org/web/education/code-of-ethics
20. ACM Code of Ethics
August 17 Kate Carruthers | UNSW 19
As an ACM member I will
1. Contribute to society and human well-being.
2. Avoid harm to others.
3. Be honest and trustworthy.
4. Be fair and take action not to discriminate.
5. Honor property rights including copyrights and patent.
6. Give proper credit for intellectual property.
7. Respect the privacy of others.
8. Honor confidentiality.
From the ACM Code of Ethics
21. Accenture: 12 guidelines for developing data ethics codes
1. The highest priority is to respect the persons behind the data.
2. Attend to the downstream uses of datasets.
3. Provenance of the data and analytical tools shapes the consequences of
their use.
4. Strive to match privacy and security safeguards with privacy and security
expectations.
5. Always follow the law, but understand that the law is often a minimum bar.
6. Be wary of collecting data just for the sake of more data.
7. Data can be a tool of inclusion and exclusion.
August 17 Kate Carruthers | UNSW 20
https://www.accenture.com/t20160629T012639__w__/us-en/_acnmedia/PDF-24/Accenture-Universal-Principles-Data-Ethics.pdf
22. Accenture: 12 guidelines for developing data ethics codes
8. As much as possible, explain methods for analysis and marketing to data
disclosers.
9. Data scientists and practitioners should accurately represent their
qualifications, limits to their expertise, adhere to professional standards,
and strive for peer accountability.
10.Aspire to design practices that incorporate transparency, configurability,
accountability, and auditability.
11.Products and research practices should be subject to internal, and
potentially external ethical review.
12.Governance practices should be robust, known to all team members and
reviewed regularly
August 17 Kate Carruthers | UNSW 21
https://www.accenture.com/t20160629T012639__w__/us-en/_acnmedia/PDF-24/Accenture-Universal-Principles-Data-Ethics.pdf
23. Some things to think about
August 17 22Kate Carruthers | UNSW
24. Privacy matters
Privacy by Design
1. Proactive not Reactive; Preventative not
Remedial
2. Privacy as the Default Setting
3. Privacy Embedded into Design
4. Full Functionality – Positive-Sum, not Zero-Sum
5. End-to-End Security – Full Lifecycle Protection
6. Visibility and Transparency – Keep it Open
7. Respect for User Privacy – Keep it User-Centric
August 17 Kate Carruthers | UNSW 23
“Privacy is an inherent
human right, and a
requirement for
maintaining the human
condition with dignity and
respect.”
- Bruce Schneier
25. August 17 Kate Carruthers | UNSW 24
Technology has no
ethics. People
demonstrate ethics.
26. August 17 Kate Carruthers | UNSW 25
Technology inherits
the biases of its
makers
27. August 17 Kate Carruthers | UNSW 26
Kent Aitken, Prime Ministers Fellow,
Public Policy Forum Canada, 2017
33. August 17 Kate Carruthers | UNSW 32
More thought is
needed!
34. Resources
Georgetown University, Kennedy Institute of Ethics, Ethics Lab
Causeit Data Ethics
The BIG Data Ethics Cheat Sheet, Hackermoon
Digital Ethics Lab - Oxford Internet Institute - University of Oxford
Guidelines on Ethical Research - British Sociological Association
What is data ethics? Luciano Floridi, Mariarosaria Taddeo. Phil. Trans. R. Soc. A 2016 374
20160360; DOI: 10.1098/rsta.2016.0360. Published 14 November 2016
Digital Enlightenment Forum: Digital Ethics. Workshop Report. (2016, March 1). Retrieved August 16, 2017, from
https://digitalenlightenment.org/sites/default/files/users/14/Digital%20Ethics%20Workshop%20Report%20v2.pdf
A deep study on the concept of digital ethics. Maggiolini, Piercarlo. (2014).. Revista de Administração de
Empresas, 54(5), 585-591. https://dx.doi.org/10.1590/S0034-759020140511
August 17 Kate Carruthers | UNSW 33