My Digital FootPrint

Woody Hartzog (Stanford)  ( personal site )  "Control is the wrong goal for privacy by design, perhaps the wrong goal for data protection in general." But isn't control a central tenet of good privacy? It sure is. But it shouldn't be, the author of "Privacy’s Blueprint: The Battle to Control the Design of New Technologies" .  While everyone emphasizes "control" of personal data as core to privacy, too much zeal for control dilutes efforts to design information tech correctly. This idealized idea of control is impossible. Control is illusory. It's a shell game.   It's mediated and engineered to produce a particular control. Design is everything. Hear Hartzog's further thoughts in this engaging presentation from Europe's largest privacy thought-leadership event.

NO TIME TO READ AI RESEARCH? WE SUMMARIZED TOP 2018 PAPERS FOR YOU reference - excellent Source : https://www.topbots.com/most-important-ai-research-papers-2018/

Source https://qz.com/1525661/your-digital-identity-has-three-layers-and-you-can-only-protect-one-of-them/amp/ My version of the concept is here  from 2009 I would add to this excellent work by  Katarzyna Szymielewicz  that it is not about me and my data and what analysis of my data tells anyone.  It is about all data, and once anything leaves my head it is shared.  There once was a (useful) set of boundaries and limits to the capability that sharing of data could produce; now there is no boundary and no limit. Get the full version  here

Source: https://futureoflife.org/valuealignmentmap/ Value Alignment Research - stunning visualisation The project of creating value-aligned AI is perhaps one of the most important things we will ever do. However, there are open and often neglected questions regarding what is exactly entailed by 'beneficial AI.' Value alignment is the project of one day creating beneficial AI and has been expanded outside of its usual technical context to reflect and model its truly interdisciplinary nature. For value-aligned AI to become a reality, we need to not only solve intelligence, but also the ends to which intelligence is aimed and the social/political context, rules, and policies in and through which this all happens. This landscape synthesizes a variety of AI safety research agendas along with other papers in AI, machine learning, ethics, governance, and AI safety, robustness, and beneficence research. It lays out what technical research threads can help us to create beneficial AI

Source : Data Science Central   By: Jennifer Lewis Priestley love the thinking, however I would put governance at the top and moral's at the bottom, ethics (as group) above morals, then maths & computer science ( as philosophies ) Then algorithms then communications. Why governance at the top, as we need to be accountable and ethics are not accountable.    

Data Governance is somewhat easier to define using wiki on 17th March 2019 Data governance is a data management concept concerning the capability that enables an organization to ensure that high data quality  exists throughout the complete lifecycle of the data. The key focus areas of data governance include availability, usability, consistency [1] , data integrity and data security and includes establishing processes to ensure effective data management throughout the enterprise such as accountability for the adverse effects of poor data quality and ensuring that the data which an enterprise has can be used by the entire organization. Data governance encompasses the people, processes, and information technology required to create a consistent and proper handling of an organization's data across the business enterprise . It provides all data management practices with the necessary foundation, strategy, and structure needed to ensure that data is managed as an asset and tran

https://i-consentproject.eu/results/ D1.1 Report on guidelines, standards and initiatives for improving informed consent in the healthcare context. D1.2 Report on gender and age-related issues associated with the acquisition of informed consent. D1.3 Ethical and legal review of the informed consent. D1.4 Ethical issues concerning informed consent in translational/clinical research and vaccination. D1.5 Legal issues concerning informed consent in translational/clinical research and vaccination. D1.6 Patient involvement in vaccine research. D1.7 Socio-cultural, psychological and behavioural perspectives towards informed consent process.