Data science used to be somewhat of a mystery, more of a dark art than a repeatable, scientific process. Companies basically entrusted powerful priests called data scientists to build magical algorithms that used data to make predictions, usually to boost profits or improve customer happiness. But in recent years, the field has matured to a remarkable degree, and that is enabling progress to be made on multiple fronts, from ModelOps and reproducibility to ethics and accountability. About five years ago, the worldwide scientific community was suffering a "reproducibility crises" that impacted a wide range of scientific endeavors, including so-called hard sciences like physics and chemistry. One of the hallmarks of the scientific method is that experiments must be reproducible and will give the same results, but that lofty goal too often was not met.

This blog post is part of a series where Portulans staff review recent developments in tech policy. Check our Twitter and LinkedIn to follow the conversation. Last month saw the launch of the Oxford Commission on AI and Good Governance, hosted by the Oxford Internet Institute (where our Board Member, Bill Dutton, is a Senior Fellow). Over the next eighteen months, OxCAIGG will contribute research and evidence-based policy recommendations to help governments and public sectors worldwide properly understand and mobilize the power and opportunities granted by machine learning and data science. To this end, the Commission unites world-leading experts on governance, technology, security and human rights.

Today: Accelerating Medical and Drug Discovery To be sure, the quality of these tools and their promise varies, but given there is already reliance on AI to accelerate disease insights and drug development, we should be accelerating work on guardrails too. Among the bigger governance challenges is assessing the reliability, safety, and fairness of such tools. In many instances, a well-designed audit framework would enable leaders to evaluate whether the system is trustworthy but this can be challenging in practice. Tomorrow: Enabling Population Management and Limiting Disease Spread Tracking COVID-19 patients and their contacts is widely understood to be central to the effort to contain spread and eventually, loosen the restrictions on our mobility and economic activity. The AI/ML-enabled contact tracing tools that were so effective in Singapore and South Korea are now, in some form, likely coming to the EU and US.

FREMONT, CA: The development in technology has accelerated growth and profits in many industries. Applications of technologies like Artificial Intelligence (AI) are so wide-ranging that it has managed to become an integral part in seemingly non-technical sectors as well. The government sector is yet to adopt advanced technologies in a manner as other areas have. This could change rapidly though, as governments are making themselves feel at home with the transforming technological landscapes. AI can bring about significant changes in the way governments work and make the public sector much more efficient than it has ever imagined being.

The emerging technologies of the Fourth Industrial Revolution (4IR) will inevitably transform the world in many ways – some that are desirable and others that are not. The extent to which the benefits are maximized and the risks mitigated will depend on the quality of governance – the rules, norms, standards, incentives, institutions, and other mechanisms that shape the development and deployment of each particular technology. Too often the debate about emerging technologies takes place at the extremes of possible responses: among those who focus intently on the potential gains and others who dwell on the potential dangers. The real challenge lies in navigating between these two poles: building understanding and awareness of the trade-offs and tensions we face, and making informed decisions about how to proceed. This task is becoming more pressing as technological change deepens and accelerates, and as we become more aware of the lagged societal, political and even geopolitical impact of earlier waves of innovation.

Not an event goes by without us talking about the impact of technology, and terms like IoT (internet of things), cloud, big data, AI (artificial intelligence) are widely touted as being the'next big things'. For example, we talk about billions of connected devices enabling smart decisions, or robots taking over many types of jobs in the future, or how artificial intelligence will solve lots of complex challenges. It's no surprise then that governments and industry thought leaders are engaged in conversations on the consequences of having all this technology integrated into everything. Research published this month by the World Economic Forum says that for emerging technologies to achieve their full potential to improve human life and address global challenges, action is needed to make sure their use is governed properly. This was echoed by a survey of the world's top technology investors at the Web Summit in Lisbon, which said governments are failing to prepare for the impact of artificial intelligence – which is set to destroy millions of jobs, according to a poll of the.

The research forms part of a survey of nearly 900 experts that is used to compile the Forum's Global Risks report. When asked which emerging technologies need better governance, two technologies were clear outliers: artificial intelligence and robotics, followed by biotechnologies. The third technology most in need of governance is energy capture, storage and transmission. Other technologies in the top 10 are blockchain and distributed ledger (4), which has been touted as having a game-changing effect on industries, from banking and financial services to agriculture. Following this is geo-engineering (5), which is often seen as a response to climate change but whose effectiveness and potential negative side effects remain largely unknown.

The research forms part of a survey of nearly 900 experts that is used to compile the Forum's Global Risks report. When asked which emerging technologies need better governance, two technologies were clear outliers: artificial intelligence and robotics, followed by biotechnologies. The third technology most in need of governance is energy capture, storage and transmission. Other technologies in the top 10 are blockchain and distributed ledger (4), which has been touted as having a game-changing effect on industries, from banking and financial services to agriculture. Following this is geo-engineering (5), which is often seen as a response to climate change but whose effectiveness and potential negative side effects remain largely unknown.