마가렛 베스티거(Margrethe Vestager) 유럽집행위원회 수석 부집행위원장의 연설문의 초반 부분입니다.
고유 명사와 삽입절을 제거한 것으로 원문과 조금 다른 부분들이 존재합니다.
Glossary:
1 turbocharging: 터보차지 (경제나 성장 등을 급격히 향상시키는 것을 의미)
2 learning curve: 학습 곡선
3 open sourcing: 오픈 소싱, 오픈 소스화 (소프트웨어나 프로젝트의 소스 코드를 공개하여 누구나 접근하고 수정할 수 있도록 하는 것을 의미)
4 frontloading: 초기 집중, 앞당겨 수행
본문:
I'm delighted to be joining you today to conclude this workshop on competition in virtual worlds and generative AI. This is a hot topic. And it's showing no signs of cooling down.
Generative AI is a transformative innovation that gives us a powerful new tool. It holds tremendous promise of turbocharging the economy, boosting growth, productivity, and competitiveness, and bringing in a new industrial revolution. The possibilities seem endless, from speeding up customer relations, administrative tasks, or software development to drug discovery and development, or personalized medical treatment plans.
What will all of this mean for us in the future? With the new opportunities come new challenges and threats. There are both pessimists and optimists, but we as competition authorities have to be realists. We act in the here and now to make markets work for people. So is there anything that we can do? And if so, what is it? We are on a learning curve, and we are facing a steep hill. That is why a workshop like today's matters so much. Because we won't make it to the top of the curve unless we go on this journey together.
We have many questions. Does AI have the power to disrupt the status quo? Will there be real competition from new challengers? Or will it remain among the established tech giants who claim intense rivalry but actually dominate the market? Will it give the big companies even more power, or could we just go from one monopoly to the next?
Will the foundation level remain concentrated and what is needed to open it up for entry? How will start-ups access the necessary inputs to develop and build their models? What about licensing and open sourcing? We have been discussing many of those questions today and step by step we are getting closer to finding answers.
What we do know for certain is that we need to find out fast what an effective governance model for AI and virtual worlds should look like. A model that can quickly fix the competitive harms in AI markets without stifling innovation.
Because now is the time to act. Strong competition enforcement is always needed at times of big industrial and tech changes. It is then that markets can tip, that monopolies can be formed, and that innovation can be snuffed out. When competition enforcement steps in, it allows different business models and new ideas to develop. So we must get ready. AI and the metaverse are developing at breakneck speed. We cannot just sit back and see how things pan out.
We are now dealing with existing market power and all the issues that come with it. Key areas of the digital economy like search, e-commerce, and social networks are almost monopolized. We need to start from this reality and make sure we don't repeat the same mistakes. We must learn from the last few decades. We need to guide these technologies so they benefit everyone. We must stop harmful practices and make sure that AI delivers on its promise.
If we want to adapt our enforcement to this new reality properly, we first need to understand the emerging AI ecosystem across various sectors of the economy. That's why competition authorities are frontloading their learning process through consultations and outreach activities like our workshop today.