The EU AI Act (the “AI Act”) is the world’s first comprehensive AI law. The Act lays down a harmonised legal framework for the development, supply, and use of AI products and services in the EU.  

To whom does the AI Act apply? 

The legal framework will apply to all AI systems impacting people in the EU, regardless of where systems are developed or deployed. 

When will the AI Act take effect? 

The AI Act is currently expected to enter into force in Q2-Q3 2024, with different obligations then taking effect in stages. 

Understanding the  AI Act’s Objectives 

The draft AI Act seeks to achieve a set of specific objectives:  

• Ensuring that AI systems placed on the EU market are safe and respect existing EU law; 
• Ensuring legal certainty to facilitate investment and innovation in AI; 
• Enhancing governance and effective enforcement of EU law on fundamental rights and safety requirements applicable to AI systems; and  
• Facilitating the development of a single market for lawful, safe, and trustworthy AI applications and preventing market fragmentation.  

AI Act: different rules for different risk levels 

The new rules establish obligations for providers and users depending on the level of risk from artificial intelligence. While many AI systems pose minimal risk, they need to be assessed. 

 
1. Unacceptable risk 

Unacceptable risk AI systems are systems considered a threat to people and will be banned.  

They include: 

• Cognitive behavioural manipulation of people or specific vulnerable groups: for example, voice-activated toys that encourage dangerous behaviour in children. 
• Social scoring: classifying people based on behaviour, socio-economic status, or personal characteristics. 
• Biometric identification and categorisation of people. 
• Real-time and remote biometric identification systems, such as facial recognition. 

Some exceptions may be allowed for law enforcement purposes. “Real-time” remote biometric identification systems will be allowed in a limited number of serious cases, while “post” remote biometric identification systems, where identification occurs after a significant delay, will be allowed to prosecute serious crimes and only after court approval. 

2. High risk 

AI systems that negatively affect safety or fundamental rights will be considered high risk and will be divided into two categories: 

1) AI systems that are used in products falling under the EU’s product safety legislation. This includes toys, aviation, cars, medical devices and lifts. 

2) AI systems falling into specific areas that will have to be registered in an EU database: 

• Management and operation of critical infrastructure 
• Education and vocational training 
• Employment, worker management and access to self-employment 
• Access to and enjoyment of essential private services and public services and benefits 
• Law enforcement 
• Migration, asylum and border control management 
• Assistance in legal interpretation and application of the law. 

 
All high-risk AI systems will be assessed before being put on the market and also throughout their lifecycle. 

3. General purpose and generative AI 
Generative AI, like ChatGPT, would have to comply with transparency requirements: 

• Disclosing that the content was generated by AI. 
• Designing the model to prevent it from generating illegal content. 
• Publishing summaries of copyrighted data used for training. 

High-impact general-purpose AI models that might pose systemic risk, such as the more advanced AI model GPT-4, would have to undergo thorough evaluations and any serious incidents would have to be reported to the European Commission. 

4. Limited risk 

Limited risk AI systems should comply with minimal transparency requirements that would allow users to make informed decisions. After interacting with the applications, the user can then decide whether they want to continue using it. Users should be made aware when they are interacting with AI. This includes AI systems that generate or manipulate image, audio or video content, for example deepfakes. 

Opportunities 

Ethical Leadership: Organisations that prioritise ethical AI practices and demonstrate a commitment to responsible innovation can enhance their reputation and build trust with consumers, employees, and regulators. By aligning with the principles of the AI Act, organisations can position themselves as leaders in ethical AI deployment. 

Innovation and Differentiation: The AI Act promotes regulatory sandboxes and real-world testing, providing opportunities for Organisations to innovate and develop AI solutions in a controlled environment. Companies that invest in compliance and develop AI systems that meet the  AI Act’s standards can differentiate themselves in the market and gain a competitive edge. 

Market Expansion: Compliance with the AI Act allows Organisations to access the European market with confidence, as they demonstrate adherence to regulatory requirements and respect for fundamental human rights. This opens opportunities for expansion and growth in a region that values ethical AI practices. 

Talent Acquisition: Companies that invest in talent acquisition and training to support AIA compliance with the AI Act can attract top-tier professionals with expertise in AI governance, ethics, and regulatory compliance. Building a skilled workforce capable of navigating the complexities of AI regulation is essential for long-term success. 

The AI Act represents a real opportunity for Organisations that are looking to leverage the power of AI. However, there are some threats that business leaders also need to consider. 

Threats: 

Compliance Costs: The AI Act imposes significant compliance costs on Organisations, including overhead expenses related to risk assessments, governance frameworks, and regulatory reporting. Companies that fail to allocate sufficient resources to the Act’s compliance may face financial strain and operational challenges. 

Fines and Penalties: Non-compliance with the AI Act can result in substantial fines ranging from €7.5 million to €35 million, or a percentage of global turnover. Organisations that neglect the AI Act’s requirements or underestimate the severity of regulatory violations risk facing severe financial penalties that could impact their bottom line and reputation. 

Operational Disruption: Implementing robust governance and oversight measures to ensure  compliance with the AI Act may require operational adjustments and process changes. Organisations that fail to adapt their operations to meet the AI Act’s standards may experience disruption and inefficiencies that hinder productivity and competitiveness. 

Reputational Damage: Violations of the AI Act’s ethical standards or failures to comply with regulatory requirements can lead to reputational damage and loss of consumer trust. Organisations that are perceived as prioritising profit over ethics or disregarding fundamental human rights may face backlash from stakeholders and damage to their brand reputation. 

Conclusion  

In conclusion, while the AI Act presents opportunities for Organisations to demonstrate ethical leadership, drive innovation, and access new markets, it also poses significant threats in terms of compliance costs, fines, operational disruption, and reputational damage. By proactively addressing these challenges and investing in compliance with the AI Act, Organisations can navigate the regulatory landscape successfully and leverage AI technologies responsibly for long-term growth and sustainability. 

For more comprehensive information on Calligo’s Data Ethics and Governance solutions, visit https://www.calligo.io

For more information on Calligo’s AI solutions, visit https://www.calligo.io

The post Navigating the EU’s proposed Artificial Intelligence Act: What Organisations Need to Know appeared first on Calligo.

Join Nick Mishko, Senior Data Analytics Team Lead at Calligo, as he delves into the world of property management analytics and Yardi data.

Discover how Calligo’s data analytics practice transforms Yardi data into powerful tools, enhancing operational efficiency for property management firms globally. From data extraction challenges to creating dynamic dashboards, explore the strategies and solutions that propel businesses forward.

If you’re navigating Yardi complexities or seeking to leverage analytics for your property management endeavours, this insightful discussion is a must-watch. Stay tuned for more insights from Calligo Shorts!

The post Unlocking Property Management Insights: Extracting and Analyzing Yardi Data appeared first on Calligo.

In this lively debate you will hear from Calligo’s Practice Leads as they discuss their key takeaways from 2023 and their data predictions for 2024 and beyond.

Topics discussed include:

The post Data Transformation Predictions for 2024 – Calligo Data Leaders Roundtable appeared first on Calligo.

Introduction 

When I started my first project with Microsoft back in 2019, I was tasked with creating a report to help a sales team understand when clients had licenses up for renewal and see detailed information about the client’s usage of licenses to help the sales team better optimize agreements with their customer base. The tool was revolutionary for the sales team, which used to pull data from several sources and spend hours making sure it was right. Reports done right can lead to huge efficiencies and make everyone’s jobs smoother, letting us focus on the decisions that truly matter. 

The problem 

With that project complete, I moved onto a new project with a different team, and then another. Two years later an email popped up from a random employee at Microsoft. He’d found the report I’d built and was asking if I could update it for him. I did a little digging and found that my old team had moved on to a new report, but the old one was still available in their portal and employees could still search for and find the report if they had the proper access. Reports and dashboards across the org had proliferated and no one was taking the time to consolidate them. As a result, people were finding old, not quite deprecated reports and trying to use outdated data to make decisions. 

The details 

This problem isn’t unique to Microsoft. If you’ve been working with data for long enough, this problem almost certainly applies to you. As people who love data, we want to see insights that are relevant to us and tailored specifically to the way we want to see the data. With multiple teams or levels viewing the same data, this can lead to custom reports for each group that all slice the data slightly differently. When metrics change, these changes don’t always make their way to every report, especially if Dave in accounting (sorry Dave!) created a copy of a report to do his own work. As time goes on, the number of reports keeps expanding and when new team members onboard they don’t know which reports have the right data. This can lead to muddy reporting environments, with reports from years ago that we keep around because we might want to see that data or that visual again someday. 

The Solution 

Are we doomed to drown in an unending deluge of reports or is there something we can do about it? 

1. Create report documentation. 

Whenever you create a report, you should create documentation that outlines the data sources, the intended audience, and how the report is intended to be used. Documentation for a report overall should be supplemented by a data dictionary that covers the measures or calculations in the report and gives everyone clarity on what is being reported. We often add these as readme tabs or store them in a company wiki. This not only helps with keeping our environments clean, but also helps new users onboard. You will never have to answer the question – “What did we use this report for?” 

2. Utilize report usage metrics. 

Power BI has built in reports that let you see which reports have been viewed and by whom. Tableau has similar features for Tableau server. We think these reports are so useful we built our own custom report that lets you see usage across workspaces or servers to help you make the decisions on what reports to deprecate. We deployed this in our own environments and for multiple customers.

Interact with the dashboard by clicking on the image below

3. Archive reports offline. 

Sometimes we don’t want to get rid of reports or need to keep them, but we don’t want them to be available to the organization. In this case, we recommend creating an archive for reports to be kept offline or at least off the workspace or server. These reports should also have accompanying documentation and a data dictionary (thank you, readme tab!) 

Closing Remarks 

Maintaining your reporting environment hygiene pays dividends in the future and reduces confusion and wasted time. In fact, we saw this as one of our trends for 2023. Curious about the other trends we saw or our predictions about 2024? Watch our Data Transformation Predictions video to see them. We take our reporting work very seriously and our team has the tools and experience to help you with your environment.

For more comprehensive insights into data analytics and visualization, visit https://www.calligo.io

The post Trends in Data Visualization Proliferation and Consolidation appeared first on Calligo.

The post Science + Data eBook appeared first on Calligo.

The post The DPO in 2023: Are Non-Compliant Organizations at Risk? appeared first on Calligo.

The post Research Report 2023: De-Risking Machine Learning Projects appeared first on Calligo.

The post Machine Learning as a Service | factsheet appeared first on Calligo.

The post Demystifying Data Success | eBook appeared first on Calligo.

The post Data Science by Design | factsheet appeared first on Calligo.