Following recent reports from the Government Office for Science and the House of Commons Select Committee, Digital Catapult comments on how access to data can open opportunities to the UK's AI entrepreneurs. Artificial Intelligence (AI) is at the centre of two recent government reports. Yesterday, the Government Office for Science published an overview of AI that focuses on several significant areas: the effect of AI on productivity and economic value, advantages to government, effects on the labour market, ethical challenges and public trust. Earlier in October the House of Commons Select Committee published their report on Robotics and Artificial Intelligence that recommends that the government is to invest in education and training infrastructures, ensure digital inclusion and governance mechanisms, and provide leadership for future growth in robotics and AI. When considering where the government can provide a significant boost to UK AI and machine learning entrepreneurs, Digital Catapult believes there is a major opportunity in access to data.

Marko Balabanovic, Chief Technology Officer at Digital Catapult, writes about the barriers facing machine learning companies, particularly when they are looking to scale. Machine learning techniques, within the field of Artificial Intelligence, are becoming increasingly effective and important for data innovators. The major challenges facing fast-growing organisations have been well documented in the Scale-Up Report, and include recruiting skilled employees, building leadership capability, accessing customer and finance, and navigating infrastructure. However, for companies whose products and services use machine learning, we see two more specific barriers: access to skilled machine learning specialists, and access to large pools of data with which to train their algorithms. Both are exacerbated by the dominant position of the "GAFA" major internet companies (Google, Apple, Facebook and Amazon), who are rapidly acquiring large machine learning teams and have many advantages in acquiring training data through the data and channels they already control.