The digital divide within countries

[rakhirhif8963]

Trust: How secure are individuals and firms in the context of the networked economy. This applies not only to crime control, but also to perceptions of security and privacy. How trusting is the environment and how trusting are the common patterns of behavior?
Regulation: The extent to which government participates in the network economy through regulation.
Inclusion: , where governance can address issues such as inequalities based on gender, disability and socio-economic status.
In this context, the meaning of cybersecurity has expanded significantly. In addition to a set of policies and tools against cybercrime, it now encompasses concepts such as confidentiality and privacy. Recent scandals (such as Cambridge Analytica) highlight the growing importance of such approaches. This work is far from over, and is considered essential to increasing (and sometimes restoring) the level of trust needed in a data-driven world.

Building trust cannot be achieved alone: ​​it requires high-level governance principles and practices. Governance frameworks (including data governance) are needed to enable society to anticipate and shape the impact of new technologies. Their absence will lead to scenarios in which the digital revolution, like any other, will eventually devour its own children. There is a growing recognition that if we fail to use technology to bring out the best in people, we could potentially face scenarios in which society is fractured and some of our core organizing principles, such as democracy, are perverted.

The COVID crisis has transformed the priority of ghana mobile database into an imperative of digitalization. In parallel, new contradictions have emerged that could lead, for example, to a split in the Internet (splinternet). Some even argue that the metaverse we see developing today is already split from the start, and that its rapid, “wild west” growth will lead to insoluble problems unless some guidelines are adopted soon.

The same can be said of the ongoing efforts to develop similar principles for the development and use of AI. As the “textual wave of innovation” (reflected in the change in language) begins to form – the one that will take us from digital transformation to the evolution of deep science – we will find it increasingly difficult to give good answers to questions that we have not yet been able to define or formulate.

Foreseeing the consequences of modern crises
As previously highlighted, the pandemic has highlighted our dependence on data and data flows. Since many of the habits and practices that emerged during these exceptional times will not disappear, the increase in data that individuals and organisations experienced will become part of the new normal. However, some of the negative aspects of this trend will need to be addressed, especially in terms of inclusion – being offline should not mean being disenfranchised – and reducing inequality, for example in the case of poorer economies and regions that face a more difficult path in terms of digital transformation.