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Inventorship of AI and Türkiye’s Position

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Inventorship of AI and Türkiye’s Position

Posted | Updated by Insights team:

Publication | Update:

Jun 2024
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Artificial intelligence has begun taking over roles normally performed by humans with little difficulty,...

Artificial intelligence has begun taking over roles normally performed by humans with little difficulty, including the act of inventing. As a result, debates on whether artificial intelligence can be the owner of an invention have emerged across the global and are likely to open many novel discussions.

The debate on whether an artificial intelligence system can be an inventor began after the development of DABUS, the artificial intelligence system developed by Dr. Stephen Thaler. A team led by Dr. Thaler and Prof. Ryan Abbott have filed applications with patent offices worldwide for two separate inventions of DABUS.

An examination of applications for DABUS’ inventions serves to illustrate developments and approaches to the issue of AI inventions at patent offices across different jurisdictions.

In July 2019, Thaler submitted patent applications for two DABUS inventions to the United States Patent and Trademark Office (USPTO), listing DABUS as the sole inventor. However, these applications were rejected on the grounds that the applications were incomplete due to the absence of a real human inventor. Following Thaler’s requested review of the decisions, the Federal District Court concluded that an “inventor” under the Patent Act must be an “individual”, and the meaning of “individual” is a natural person and also emphasized that inventorship is a concept that requires a mental act and thus, an AI cannot be the inventor. Thaler appealed the decision in 2022, and, subsequently, the Supreme Court held that “individual” refers to human beings, and therefore “inventors” must be human beings.

The United Kingdom Intellectual Property Office (UKIPO) rejected Thaler’s DABUS applications on the grounds that DABUS is not a “person”, and, thus, cannot be considered as the inventor. The UK High Court and the Court of Appeal upheld this decision of the UKIPO. A subsequent appeal to the UK Supreme Court was rejected by the Court’s on the 20th of December 2023. The decision of the Court concluded that artificial intelligence is not a “person” and for this reason cannot be considered the owner of the invention.

Similarly, Thaler filed two European patent applications with the European Patent Office (EPO) in 2018, both of which were rejected upon EPO’s determination that the inventor designated in a European patent must be a “natural person”. Following the request for review by Thaler, the Legal Board of Appeal stated in its preliminary opinion that under the European Patent Convention, the inventor designated in a patent application must be a person with legal capacity. In December 2021, the Legal Board of Appeal dismissed Thaler’s appeal. Thaler’s divisional application, where he is named as the inventor, remains pending before the EPO.

The German Federal Patent Court took a different perspective on the issue of AI inventorship regarding DABUS applications. Upon an appeal filed before the Federal Patent Court concerning the rejection of Thaler’s application to the German Patent Office, the Court acknowledged that AI inventions are patentable but stipulated that the inventor must be presented as a natural person in the application. This decision is significant, as it made it possible to include AI’s involvement in a patent application, sidestepping the debate over who could be deemed the inventor. The Court set out that the one responsible for the invention must be identified as the inventor on the relevant paperwork, and details regarding the contribution of an AI system may be added as additional information.

While there is no specific regulation addressing the inventorship of artificial intelligence in Turkish Law, it is vital to note that there have been no legal precedents in Türkiye akin to the cases concerning DABUS patent applications, nor have there been any applications to the Turkish Patent and Trademark Office designating AI as the inventor.

Yet, Türkiye’s approach is expected to be similar to that of the EPO. Indeed, if the DABUS applications filed before the EPO (which also encompasses Türkiye) had been registered by the EPO instead of being rejected, the patents in question would now be registered before the Turkish Patent and Trademark Office in accordance with the European Patent Convention.

The basis of the problems discussed in Türkiye (as in many other countries) regarding the inventorship of artificial intelligence lies in the determination of the legal status of the AI and the introduction of special legal regulations and precedence on the issue. Designating AI as the inventor in patent applications will pave the way for artificial intelligence to be recognized as the patent owner. In such a case, this will mark the beginning of a new era in patent law, especially in liability law.

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The future outlook “forecast” is based on a set of statistical methods such as regression analysis, industry specific drivers as well as analyst evaluations, as well as analysis of the trends that influence economic outcomes and business decision making.
The Global Economic Model is covering the political environment, the macroeconomic environment, market opportunities, policy towards free enterprise and competition, policy towards foreign investment, foreign trade and exchange controls, taxes, financing, the labour market and infrastructure. We aim update our market forecast to include the latest market developments and trends.

Forecasts, Data modelling and indicator normalisation

Review of independent forecasts for the main macroeconomic variables by the following organizations provide a holistic overview of the range of alternative opinions:

  • Cambridge Econometrics (CE)

  • The Centre for Economic and Business Research (CEBR)

  • Experian Economics (EE)

  • Oxford Economics (OE)

As a result, the reported forecasts derive from different forecasters and may not represent the view of any one forecaster over the whole of the forecast period. These projections provide an indication of what is, in our view most likely to happen, not what it will definitely happen.

Short- and medium-term forecasts are based on a “demand-side” forecasting framework, under the assumption that supply adjusts to meet demand either directly through changes in output or through the depletion of inventories.
Long-term projections rely on a supply-side framework, in which output is determined by the availability of labour and capital equipment and the growth in productivity.
Long-term growth prospects, are impacted by factors including the workforce capabilities, the openness of the economy to trade, the legal framework, fiscal policy, the degree of government regulation.

Direct contribution to GDP
The method for calculating the direct contribution of an industry to GDP, is to measure its ‘gross value added’ (GVA); that is, to calculate the difference between the industry’s total pre­tax revenue and its total bought­in costs (costs excluding wages and salaries).

Forecasts of GDP growth: GDP = CN+IN+GS+NEX

GDP growth estimates take into account:

  • Consumption, expressed as a function of income, wealth, prices and interest rates;

  • Investment as a function of the return on capital and changes in capacity utilization; Government spending as a function of intervention initiatives and state of the economy;

  • Net exports as a function of global economic conditions.

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Market Quantification
All relevant markets are quantified utilizing revenue figures for the forecast period. The Compound Annual Growth Rate (CAGR) within each segment is used to measure growth and to extrapolate data when figures are not publicly available.

Revenues

Our market segments reflect major categories and subcategories of the global market, followed by an analysis of statistical data covering national spending and international trade relations and patterns. Market values reflect revenues paid by the final customer / end user to vendors and service providers either directly or through distribution channels, excluding VAT. Local currencies are converted to USD using the yearly average exchange rates of local currencies to the USD for the respective year as provided by the IMF World Economic Outlook Database.

Industry Life Cycle Market Phase

Market phase is determined using factors in the Industry Life Cycle model. The adapted market phase definitions are as follows:

  • Nascent: New market need not yet determined; growth begins increasing toward end of cycle

  • Growth: Growth trajectory picks up; high growth rates

  • Mature: Typically fewer firms than growth phase, as dominant solutions continue to capture the majority of market share and market consolidation occurs, displaying lower growth rates that are typically on par with the general economy

  • Decline: Further market consolidation, rapidly declining growth rates

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The Global Economic Model
The Global Economic Model brings together macroeconomic and sectoral forecasts for quantifying the key relationships.

The model is a hybrid statistical model that uses macroeconomic variables and inter-industry linkages to forecast sectoral output. The model is used to forecast not just output, but prices, wages, employment and investment. The principal variables driving the industry model are the components of final demand, which directly or indirectly determine the demand facing each industry. However, other macroeconomic assumptions — in particular exchange rates, as well as world commodity prices — also enter into the equation, as well as other industry specific factors that have been or are expected to impact.

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The principal explanatory variable in each industry’s output equation is the Total Demand variable, encompassing exogenous macroeconomic assumptions, consumer spending and investment, and intermediate demand for goods and services by sectors of the economy for use as inputs in the production of their own goods and services.

Elasticities
Elasticity measures the response of one economic variable to a change in another economic variable, whether the good or service is demanded as an input into a final product or whether it is the final product, and provides insight into the proportional impact of different economic actions and policy decisions.
Demand elasticities measure the change in the quantity demanded of a particular good or service as a result of changes to other economic variables, such as its own price, the price of competing or complementary goods and services, income levels, taxes.
Demand elasticities can be influenced by several factors. Each of these factors, along with the specific characteristics of the product, will interact to determine its overall responsiveness of demand to changes in prices and incomes.
The individual characteristics of a good or service will have an impact, but there are also a number of general factors that will typically affect the sensitivity of demand, such as the availability of substitutes, whereby the elasticity is typically higher the greater the number of available substitutes, as consumers can easily switch between different products.
The degree of necessity. Luxury products and habit forming ones, typically have a higher elasticity.
Proportion of the budget consumed by the item. Products that consume a large portion of the consumer’s budget tend to have greater elasticity.
Elasticities tend to be greater over the long run because consumers have more time to adjust their behaviour.
Finally, if the product or service is an input into a final product then the price elasticity will depend on the price elasticity of the final product, its cost share in the production costs, and the availability of substitutes for that good or service.

Prices
Prices are also forecast using an input-output framework. Input costs have two components; labour costs are driven by wages, while intermediate costs are computed as an input-output weighted aggregate of input sectors’ prices. Employment is a function of output and real sectoral wages, that are forecast as a function of whole economy growth in wages. Investment is forecast as a function of output and aggregate level business investment.

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