Familiar debate, now with an AI twist. Can you conceive of a ‘good guy’ Terminator?

https://link.springer.com/article/10.1007/s43681-021-00113-9

The double-edged sword of AI: Ethical Adversarial Attacks to counter artificial intelligence for crime

Artificial intelligence (AI) has found a myriad of applications in many domains of technology, and more importantly, in improving people’s lives. Sadly, AI solutions have already been utilized for various violations and theft, even receiving the name AI or Crime (AIC). This poses a challenge: are cybersecurity experts thus justified to attack malicious AI algorithms, methods and systems as well, to stop them? Would that be fair and ethical? Furthermore, AI and machine learning algorithms are prone to be fooled or misled by the so-called adversarial attacks. However, adversarial attacks could be used by cybersecurity experts to stop the criminals using AI, and tamper with their systems. The paper argues that this kind of attacks could be named Ethical Adversarial Attacks (EAA), and if used fairly, within the regulations and legal frameworks, they would prove to be a valuable aid in the fight against cybercrime.

Speed. The first requirement for security software.

https://venturebeat.com/2021/10/30/security-ai-is-the-next-big-thing/

Security AI is the next big thing

… Perhaps the most compelling use case for AI in cybersecurity is incident response. AI enables organizations to automatically detect anomalous behavior within their environments and conduct automated responses to contain intrusions as quickly as possible.

… Keeping up with the latest threats isn’t the only compelling use case that AI has within cybersecurity. AI also offers the ability to automatically process and categorize protected data so that organizations can have complete transparency over how they process this data; it also ensures that they remain compliant with data privacy regulations within an ever-more-complex regulatory landscape.

“Our regulatory department tells me we evaluate 250 new regulations daily across the world to see what we need to be in compliance, so then take all of that and think about all the different laws that are being passed in different countries around data; you need machine-learning capabilities,” Johnson said.

Interesting. Using minimal information you provide then searching for (or purchasing) more data to improve your dossier… How common, I wonder…

https://www.pogowasright.org/privacy-breach-class-action-commenced-against-media-giant-rogers/

Privacy Breach Class Action Commenced Against Media Giant Rogers

The following is a press release from an attorney firm. My sites generally do not post attorney advertising but there is a news angle to this one that has potential impact for many people. DataBreaches.net emailed Rogers yesterday requesting a comment on the lawsuit, but received no reply.

TORONTO, Oct. 29, 2021 (GLOBE NEWSWIRE) — On October 26, 2021, a proposed $20 million nation-wide privacy breach class action lawsuit was commenced against Rogers Communications Inc. The claim alleges that Rogers regularly and surreptitiously invades the privacy of its customers to advance its own marketing promotional goals. In particular, it checks the credit information of its customers in order to assess customers’ suitability for marketing additional services to them.

Financial information such as credit scores is highly sensitive and confidential information that can only be accessed by companies for limited purposes – which does not include advancing the companies’ own profits through such things as targeted marketing, absent informed consent from the consumer.

The proposed class action was commenced by Rogers’ customer, David Trueman, who discovered that his credit information was accessed by Rogers no less than three times in a single calendar year. After multiple attempts by Mr. Trueman to obtain answers from Rogers about why it had been pulling his credit information, eventually Rogers explained that the credit information was accessed for “marketing and promotional purposes” and “to evaluate eligibility for other Rogers’ products and services” – despite the fact that Mr. Trueman did not apply for additional services when the credit checks were made. Mr. Trueman asserts that he did not consent to Rogers conducting any credit checks after he originally signed up for its services.

In the claim, Mr. Trueman alleges that Rogers secretly and repeatedly collects its customers’ credit information for its own marketing purposes. He asserts that this is a breach of the customers’ privacy, and contrary to privacy protection legislation across the country.

Mr. Trueman seeks damages and other remedies on behalf of a class of all Rogers customers across Canada whose credit information was similarly accessed by Rogers without their consent.

The law firm of Waddell Phillips PC represents Mr. Trueman. More information is available at www.rogersclassaction.ca.

Is AI too smart to get caught?

https://atr.dvfu.ru/jour/article/view/226

Application of Artificial Intelligence for Criminal Purposes from Criminal Law perspective

Artificial Intelligence is actively used in many areas of human life. The use of artificial intelligence systems increases the efficiency of activities, reduces costs, and increases productivity. It is assumed that such a productive tool will soon be actively used for criminal purposes. The article analyzes the concept of "artificial intelligence" and its distinctive characteristics. The author concludes that modern artificial intelligence systems are trained, not programmed, which reduces the feasibility of imposing liability on the programmer for the damage caused by such systems. The paper analyzes the properties of artificial intelligence, which may affect the degree of social acts committed with it. Among such properties, the author highlights autonomy as the ability of intelligent systems to act and make decisions independently of humans. Opacity is yet another characteristic property of modern artificial intelligence systems. It can manifest itself as inaccessibility of algorithms, source code, trained neural networks, or architecture due to their legal protection as intellectual property or state secrets. Opacity is contingent on the fact that understanding the program code and architecture of artificial intelligence systems require special knowledge and skills. In addition, understanding the work of some systems is beyond human capabilities. [Strongly disagree. Bob] The analysis shows that artificial intelligence systems increase the degree of public danger of a criminal act. First, intelligent systems create a sense of security for the criminal when committing crimes through AI. A computer program serves as a buffer between the perpetrator and the victim. The perpetrator has no contact with the victim to commit a socially dangerous act. Anonymity and impersonality when using an intelligent system by a criminal allow him/her to pass off as a different person, hide from justice, and remain outside of public censure and condemnation.

How to actually do it!

https://aisel.aisnet.org/icis2021/ai_business/ai_business/10/

From Ethical AI Principles to Governed AI

This study explores how organizations translate principles of ethical artificial intelligence (AI) into practice. To date, the research on AI ethics has been mostly conceptual, with a significant emphasis on defining the principles of ethical AI. Thus, there is momentum for a shift from principle-based ethics toward an increased focus on the implementation of ethical principles in practice. In this study, we analyzed data collected through a set of expert interviews in organizations deploying AI systems. We identified that ethical AI principles are implemented through four sets of practices: i) governance, ii) AI design and development, iii) competence and knowledge development, and iv) stakeholder communication. As our contribution to IS research, we empirically elucidate how the principles of ethical AI are translated into organizational practices. For IS practice, we provide organizations deploying AI with novel insights on how to govern their AI systems.

Tools & Techniques

https://www.makeuseof.com/tag/top-5-free-ocr-software-tools-to-convert-your-images-into-text-nb/

7 Best Free OCR Software Apps to Convert Images Into Text

… Optical character recognition (OCR) software converts pictures, or even handwriting, into text. OCR tools analyze a document and compare it with fonts stored in their database, and/or by noting features typical of characters. Some OCR apps also put it through a spell checker to “guess” unrecognized words. 100% accuracy is difficult to achieve, but a close approximation is what most software strives for.