Over the last years, AI applications have come to play a role in many security‐related fields. CSS Director Andreas Wenger and Sophie-​Charlotte Fischer show in this article that scholars who want to study AI’s link to power and security should widen their perspective to include conceptual approaches from science and technology studies (STS).

In this article, the authors introduce two STS‐inspired concepts and show how the study of AI and security could benefit from them. Finally, they focus on AI in the context of Switzerland to underscore what aspects the two previously introduced concepts help to highlight, which might remain invisible for traditional approaches.

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Amazon Web Services (AWS) has revealed new and updated courses for partners in the areas of advanced migration, security governance and machine learning.  

Among the new courses the cloud vendor has made available via its AWS Training and Certification function is AWS Solutions Training for Partners: Advanced Migrating to AWS (Technical), an advanced course that provides prescriptive guidance on how to migrate workloads at scale.  

This course also covers common migration patterns and challenges in large-scale migrations.  

With this course, partners will learn how to identify use cases for re-hosting, re-platforming and re-factoring legacy applications to AWS Cloud. Partners will also learn how to determine which applications are good candidates for automated modernisation.

Also available is the AWS Solutions Training for Partners: Security Governance at Scale (Business) course, which is designed to help sales and business professionals learn how to qualify customer opportunities around security governance at scale.  

This course covers topics such as AWS account management, cost control, security and compliance through automation, along with best practices for establishing an automated, simplified, and secure framework for governance at scale.  

AWS has also launched a major update to its AWS Solutions Training for Partners: Machine Learning on AWS (Business) digital course.

This update will see partners learn how to identify and qualify customer machine learning (ML) opportunities, how to help customers navigate the ML solution-building process and how to use such experience to build an AWS ML solutions practice.

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Although both local and federal governments have been relying on natural language processing and chatbots for seamless communication, full-fledged adoption of artificial intelligence is still a far-fetched idea. The governments would require significant time and cost investments before AI is extended to the many facets of governance.

What’s new for the government, however, is the thorough utilization of machine learning for training particular chatbots. Doing so, governments are able to deliver reliable and visible outcomes. Further, with natural language processing, they can decrypt unstructured texts and this capability can be of help in fraud detection and other related areas. The perks of using AI being multitudinous, governments should not only focus on leveraging AI but also start mapping their future course of action keeping AI in mind. In a world which is dependent on data, if governments do not use AI, it won’t be long before governments would lose the grip over the affairs of the state. In this scenario, government can act as both practitioners of AI and co-creators, building the right foundation for third party vendors and developers to set the country in the right direction of data.

Although AIis considered a threat to jobs, many AI evangelists breathe confidence in this nascent tech innovation. It is surprisingly, a job creator, according to AI proponents. With automation growing across verticals and horizontals in private and public sectors, numerous job openings can be expected to be rolled out. Asa win-win case for governments, they will be able to provide more jobs to public, and at the same time leverage AI to make lives better. Using advanced analytics and intelligence, many problems can be solved and noticeable progress can be carried out by governments. It won’t be wrong to say that in the upcoming fanfare of robots, people will have better lifestyles and access to powerful tools that will rejuvenate the seeds of comfort throughout lifestyles.

Another striking fact about AI is its ability to solve the most pressing problems faced by various communities. Considering the recent global debates that revolve around people not wanting AI to make real-time decisions, the AI enthusiasts continue to convince global populace about how AI can ameliorate the quality of human life and not control it. Governments should realize the amount of control that AI functions should have.

Governments should focus on the problem, and how they can use the technology to curb that problem. In case of AI, progress is visible, but is slow. Governments have to make sure that when they trust confidential and classified information on a technology, the technology must be fool-proof un-breach-able, secure, accurate, and transparent. Governments should hire efficient agents who will be able to control the data that is exposed to technology. They should understand information management, get used to the policies and social allowances of data, and then leverage the technology to generate desired outcomes.

Considering all these factors, it won’t be wrong to say that it may take a few more decades for governments to completely incorporate AI. In the days ahead, most likely AI will be considered as a consolidated technology which is the integration of other small technologies and run-time applications. In future, new versions of AI will come up, and the society will witness that governments are doing their best to keep pace with these latest technological advancements.

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