AI (Artificial Intelligence) technology is now poised to transform every industry, just as electricity did 100 years ago. Between now and 2030, it will create an estimated $13 trillion of GDP growth.
There are many great examples of AI showing improvements in business, life and society, such as improved medical diagnosis, self-driving cars, automatic translation, personalisation of products and services, supply-chain optimization, management of humanitarian disasters, climate change, to name just a few.
At MorphL, we’re using AI/ML for more than a year to optimize digital products and services, to improve the customer relation and experience, and to help improve operations of our B2B customers. We recognize that such powerful technology raises equally powerful questions about its use. The application of AI technology may lead to unfair or discriminatory results if the person or team that designs or implements the services is not cautious and aware of potential unwanted outcomes.
We acknowledge that this area is dynamic and evolving, and we will approach our work with humility, a commitment to internal and external engagement, and a willingness to adapt our approach as we learn over time.
We believe that technology should adapt to human behavior just as humans adapted to technology throughout centuries and that a good digital experience is personal & speaks to the individual. We started MorphL with the mission of democratizing AI and putting it in the hands of people that build digital products or services, that believe their users deserve a superior experience and that want to offer them a personalized digital experience.
AI | ML | DL technology stacks are complicated systems to tune and maintain, expertise is limited, and one minimal change of the stack can lead to failure. The AI | ML | DL market needs to go through a “standardization” process in order to create AI | ML | DL platforms that enable organizations of all sizes to build their own sources of customer, business and financial differentiation.
To help accelerate democratization, we’ve created MorphL Community Edition where we simplify AI | ML | DL projects and accelerate time-to-value by pre-integrating the necessary building blocks. No longer is a siloed knowledge group of specialists required to stand up your AI | ML | DL environments. Instead, organizations can focus their valuable data engineering and data science resources on creating new sources of customer, business and operational value.
People and computers have been working together for decades now, collectively, acting more intelligently than any single person or group of individuals has ever done before. We’re now entering a new era of AI-enabled collective intelligence one where humans and AI need not be competitors, especially when they can do so much more working together.
MorphL is being built by humans for humans and everything we do at MorphL implies a strong partnership between humans and AI: computers doing what is easiest for computers to do (automation) and people focusing on the big picture, focusing on the strategic parts of the job. Broadly speaking, through our work at MorphL, we aim at complementing human expertise, creativity and judgment. And this has implications across many different industries or professions.
We will be explicit about the kind of personal and/or non-personal data the AI systems uses as well as about the purpose the data is used for. When people directly interact with an AI system, we will be transparent to the users that this is the case. When AI systems take, or support, decisions we take the technical and organizational measures required to guarantee a level of understanding adequate to the application area. In any case, if the decisions significantly affect people's lives, we will ensure we understand the logic behind the conclusions. This will also apply when we use third-party technology.
Data protection and privacy are a corporate requirement and at the core of every product and service. We communicate clearly how, why, where, and when customer and anonymized user data is used in our AI software. This commitment to data protection and privacy is reflected in our commitment to all applicable regulatory requirements as well as through the research we conduct in partnership with other companies to develop the next generation of privacy-enhancing methodologies and technologies.
AI algorithms and datasets can reflect, reinforce, or reduce unfair biases. We recognize that distinguishing fair from unfair biases is not always simple, and differs across cultures and societies. We will seek to avoid unjust impacts on people, particularly those related to sensitive characteristics such as race, ethnicity, gender, nationality, income, sexual orientation, ability, and political or religious belief. We design AI tools to complement the human experience in a positive way and consider all types of human experiences in this pursuit. Diversity of perspective will lead to AI complementing experiences for everybody, as opposed to a select few.
We will design AI systems that provide appropriate opportunities for feedback, relevant explanations, and appeal. Our AI technologies will be subject to appropriate human direction and control. Humans should choose how and whether to delegate decisions to AI systems, to accomplish human-chosen objectives.
We will continue to develop and apply strong safety and security practices to avoid unintended results that create risks of harm. We will design our AI systems to be appropriately cautious, and seek to develop them in accordance with best practices in AI safety research. In appropriate cases, we will test AI technologies in constrained environments and monitor their operation after deployment. We develop products responsibly and do not take advantage of your products’ users by manipulating them through AI’s vastly more predictive capabilities derived from user data.
Technology can be used for good or for bad and we world’s history supports this thesis. At MorphL we work to limit potentially harmful or abusive applications. As we develop and deploy AI technologies, we will evaluate likely uses in light of the following factors: