Exploring the fallibility & trustworthiness of AI: Can we really rely on Artificial Intelligence?

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Understanding the hype & reality of AI

Artificial Intelligence (AI) has undoubtedly become one of the most significant technological advancements to date. Its potential to revolutionise industries, automate processes, and enhance decision-making has sparked excitement and curiosity among professionals, as well as the general public. However, amidst the hype surrounding AI, it is essential to consider its limitations and challenges to understand whether we can genuinely rely on this transformative technology.

In the last year, AI has made substantial progress in various fields, such as healthcare, finance and customer service. The algorithms that power AI allow the technology to learn from data input and as a result make decisions automatically. These capabilities have made AI hugely popular among many industries and organisations seeking to optimise their day-to-day operations. 

However, there are some negatives to AI which will be discussed in this blog – but do they outweigh the good? This leads us to the important question of “Is AI fallible or trustworthy?”

AIs limitations & challenges

While AI has shown remarkable capabilities, it is important to acknowledge its limitations. A significant issue is that AI lacks human-like decision-making functions, causing a difference in its decision-making process compared to humans. This difference can lead to inconsistencies between AI-generated results and human expectations, potentially resulting in unwanted outcomes. It is also important to note that while AI appears to act on its own, data scientists are still extremely important as they are required to input the information the technology runs on.

Relying solely on AI can be risky, especially when building an entire business around it. Businesses need to develop strategies for managing AI failures and ensuring that human oversight is always available when needed – helping to avoid any detrimental damage or delay to business operations if there is an outage on their chosen AI system. 

A final point to consider when using AI is that it will always be outdated. As human knowledge is gained faster than it can be transferred into the databases, it is impossible to update it at the same speed – the latest version of ChatGPT is currently running on data from September 2021. While this is not detrimental to its functionality it is important to be wary of this. 

Robust testing, reliable results & vulnerability

To ensure the trustworthiness of AI-generated results, it is essential to conduct thorough testing and validation procedures. Circling back to data scientists and their role in developing AI; they are in charge of creating the criteria for what constitutes “good” and “bad” data when it comes to AI models. There is only so much input humans can have so it is important that users of the technology ensure the accuracy of their questions, making it easier for AI to reach a reliable answer. 

The integration of AI in DevOps and DevSecOps teams also requires careful planning and consideration. It is essential for developers to identify potential vulnerabilities and address security concerns – as advanced as AI systems may seem, they are not immune to cyber threats and breaches can potentially lead to an alteration in the decision-making processes. 

The balance between embracing AI & ensuring accountability 

While AI continues to offer great potential, it is vital to find a balance between embracing its benefits and ensuring accountability for its fallibility. The idea of AI completely taking over human jobs may be exaggerated, as it is more likely to complement human abilities rather than replace them.

AI’s real value lies in its ability to handle mundane tasks and mirror human decision-making. By understanding the limitations and challenges of AI, organisations can make informed decisions about its implementation and leverage its potential while mitigating risks. However, it can be tricky to know exactly what to do to avoid such risks by using a generalised AI system. It is advised that businesses that are using AI use a specialised approach to automation in order to keep their technology secure. 

Cloudhouse has been successfully offering a solution that does exactly that for years – Guardian is a configuration drift detection and management system that allows businesses to continuously monitor all of the systems within their estate for updates, compliance changes and potential threats. Giving businesses the visibility of their systems and allowing them to manage progress and change while improving their security level. AI requires careful management, human oversight, and robust testing to ensure its reliability and trustworthiness. As AI continues to evolve, our understanding of its capabilities and limitations will play a crucial role in maximising its benefits while minimising potential drawbacks.

To discover how Cloudhouse can help you, get in contact today. 


About Cloudhouse

Avatar photoCloudhouse is experienced in problematic application migration and config monitoring systems to fix the unfixable and modernise any IT estate – whether it’s run on-premises or in the cloud. With two proven solutions; Alchemy: Cloudhouse Application Packaging Solution modernises IT estates by fixing unfixable apps and moves them onto a supported operating system.

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Cloudhouse costs are split into two elements – the licensing required to deploy application compatibility packages, and the professional services needed to create the application compatibility packages.

Licensing is offered on a per user basis for desktop applications and a per server basis for server applications. There are discounts available based on volumes.

Professional Services costs are dependent on the nature and complexity of the application. We quote a cost for packaging once we have been able to see the application, or portfolio of applications.

Contact us here with your requirements and we will provide you with a quote.

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Cloudhouse provide the Professional Services to package applications.

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Cloudhouse recommend packaged applications are tested in the standard UAT environments used for natively installed applications, or applications packaged in App-V. The more representative the test environment is of the live environment, the greater the chance of finding any issues prior to go-live.

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Service packs and updates can be applied to the applications in a package using the Editor, refer to Updating, Editing and Maintaining Containers which describes how a new snapshot is created for the update, and how it is then applied to the package.

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Cloudhouse recommends the same team who manage the operations of native apps.

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The Cloudhouse Package does not include OS components, it only contains the packaged application plus Cloudhouse components. Cloudhouse recommend the same team that is responsible for supporting applications packaged with App-V, or delivered as natively installed applications, support Cloudhouse Application Compatibility Containers.

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Cloudhouse offers a full packaging service that can scale to meet any requirement. In the event, however, that a partner wishes to offer application compatibility packaging as part of a wider solution, Cloudhouse will work with that partner. Please contact us here for details.