What is artificial intelligence and can machines think? In 1950, Alan Turing developed a test to assess a machine’s intelligence. This test, which became known as the “Turing test,” consisted of a rater, a human subject, and a machine. The evaluator had to ask questions and classify a machine as intelligent if the evaluator could not distinguish the machine’s response from the human’s.
The Organization for Economic Co-operation and Development defines artificial intelligence as a machine-based system that “for a specified set of human-defined goals can make predictions, recommendations, or decisions that affect real or virtual environments.” But what is the current status of the introduction of AI technology?
Digital trends like AI are transforming economies, governments and societies; Such technological change is transforming the way people interact with their governments and requires a shift in how public services are designed and delivered. Governments must use digital technologies to deliver timely, proactive and inclusive public services. The innovative and collaborative approaches of digitization create more trust in public institutions.
However, the AI disruption caused by digitization is also having an impact on the labor market. The OECD estimates that 9% of jobs in member countries will be automated, while another 25% will be profoundly transformed. In this context, Africa is more affected by the adoption of AI solutions and automation: 85% of jobs in Ethiopia are at risk of being replaced by automation, while in South Africa the figure is 67%.
In the context of tax revenue mobilization and collection, below we will explain how AI is an opportunity for African tax authorities, but why several key challenges need to be addressed before moving forward.
Opportunities and potential of AI in the African context
Recent acceleration in AI
AI has evolved significantly since the Turing test and since John McCarthy defined AI and is considered its father. The AI environment has evolved with the Internet of Things and Industry 4.0, where huge amounts of data from electronic devices, sensors, devices, machines and vehicles have become available.
The availability of big data fueled the development of machine learning and deep learning in the 1990s and into the 21st century. It is therefore not necessary to feed machines with rules, since machines themselves learn from the huge amounts of data and create new perspectives.
In the area of public sector services, AI can help governments design better policies, make better decisions, streamline communication with all stakeholders, accelerate the delivery of services to citizens, and shift civil servants’ work from routine jobs to high-level tasks to relocate. valuable tasks.
In Africa, AI is already being used in conflict-prone areas on the battlefield to combat insurgents, rebels and terrorists. But what are the other areas where AI is used?
A tool to use development projects
On October 26, 2019, the African ministers responsible for information and communication technologies adopted the African Digital Transformation Strategy. The DTS for Africa aims to drive digital transformation and cross-cutting themes to support the digital ecosystem.
One of the DTS’s recommendations was the creation of a working group on AI to explore creating a common African stance with capacity building and targeted projects.
The first meeting of the African Union Working Group on Artificial Intelligence was held in Cairo in December 2019, where priorities for AI for Africa were identified and a discussion took place on the use of AI to overcome development barriers and challenges.
This first session was followed by a second session in February 2021, where the working group emphasized the importance of sharing experiences and working together to bridge the digital divide between developed and African countries. The working group also stressed the importance of developing a common framework for capacity building in Africa to foster digital and AI development.
Importance of digital foundations in Africa
But the application of AI is not a reality in most African countries, with the exception of Kenya, South Africa, Nigeria, Ghana and Ethiopia. The key success factors necessary for AI development in Africa are generally absent, such as reforms in data collection and privacy, infrastructure, education and governance.
The above reform requirements are essential for AI to promote “sustainable development and inclusive growth”. They are the reasons why African countries are struggling to meet AI requirements. These requirements include digital foundations, including the availability of large amounts of data – big data – and specific skills of human adopters, which most African countries are currently struggling to meet.
Two proposals for African tax authorities with AI
Tackling the legal challenges of AI
As a new tool that can change the practice of tax law, tax authorities will do well to examine the risks of such integration of AI into tax law, especially legal risks.
Indeed, AI poses a threat to the sustainability of tax systems, despite the wide range of technological opportunities it offers. AI integrated into tax systems involves the processing of taxpayers’ personal data disclosed by taxpayers or collected from other sources by tax authorities and calls for consideration of the General Data Protection Regulation. The GDPR also applies when tax authorities use AI for profiling and automated decision-making.
So far, soft and hard law instruments on AI may not sufficiently address the specific information needs of the tax area. Adequate protection of taxpayers’ rights requires the use of explainable AI, which can make the functioning and decisions of tax AI systems understandable for taxpayers, administrative bodies and courts. Tax authorities are constitutionally responsible for miscalculations of taxes or misidentification of tax risks arising from their use. Such errors can result from programming errors (bugs).
A new source of tax revenue – AI and robots
It’s a recent suggestion that AI should pay taxes, as tax systems tend to encourage automation, while tax revenues can still come from labor income. But AI is replacing human labor and is likely to result in a loss of payroll taxes for governments in the long run. Tax systems must then be progressively redesigned to tax capital instead of labour.
To a lesser extent, introducing an “automation tax” could help slow the adoption of automation technologies and give workers and social support systems time to adapt. An automation tax could be based on changes to existing depreciation rules or capital allowances that reduce the tax incentives associated with developing and implementing AI.
On a larger scale, it is possible to allow robots (i) as a form of consumption of goods or services, (ii) for income earned as a factor of production, (iii) a write-off from the income tax base for the depletion of value, or (iv) as a combination of all three, which is more likely to occur. From a policy point of view, the possibilities for taxing robots seem numerous, but the design of robot taxation may depend on how it is perceived – whether as labor or as capital – although both forms can be considered.
One should remember that AI is a natural tax avoider. If it is too closely linked to a taxing jurisdiction, it can simply be changed so that it remains non-taxable in that jurisdiction. In the future, AI taxation will inevitably call into question the definition of “permanent establishment”. To be continued …
This article does not necessarily represent the opinion of Bloomberg Industry Group, Inc., the publisher of Bloomberg Law and Bloomberg Tax, or its owners.
Information about the author
Anton Assassa is an Associate Member of the Chartered Institute for Securities & Investment with more than 12 years of experience in Africa and Asia (Cameroon, Comoros, Democratic Republic of the Congo, Laos) in revenue mobilization and revenue collection reforms. He attended the International Specialization Cycle in Tax and Customs Administration at the École Nationale d’Administration, Paris.
Elie Sawaya led several government reforms in Asia and Africa and is a digital, private and public sector expert working for GIZ with more than 20 years of experience in public-private dialogue, e-government, private sector development, port community systems, supply chain and international trade works facilitation, electronic tax systems, risk management, customs and cross-border trade.
The authors can be contacted at: [email protected]; [email protected]
