Open letter to AI Startups and AI researchers

Update 11.2020: It is clear now that the crisis is pushing digitalization needs with an unprecedented demand across all fields and that the shape of the company, the world and economy will look very different from the one before COVID. The way we work is changing, the way we interact is changing, the way we buy and do things are also different and slowly are evolving to a new normal state.
For a company to survive in the new normal, there is an imperative need to foster an organizational culture of rapid adaptation through digitalization into all domains. Also, to create a work environment with less top-down structure of control and with silos of information, towards a team work collaboration, based on trust, with clearer purposeful aims and encouraging the teams in achieving a better emotional quotient within it. The more receptive to these aspects the companies are, the more the better the transition to the new normal will be.

Original text 03.2020: The actual COVID-19 crisis has a lot of lessons to teach us. And we have nothing learned from past pandemics. We’re just falling a downward spiral of human and economic depression. We are living with the hope that this fall will end soon and that we can recover fast. This remains to be seen but besides the many scenarios, we can say for sure that we (as EU to local administrations) were not prepared for the pandemic fight.

My criticism here is simple and only towards the AI field in which investors, CEOs, funding parties, stakeholders, must accept the failure in serving the vital interests, human needs and a failure to set these priorities. In old programming therms, it’s like we are developing a nice GUI, with no good business logic, no solid platform, obsolete middle tier connections. There is no way to advance here until we are not addressing the base layers.

Every single AI researcher should from now on follow a new AI ethic book and focus on what is essential first. The AI research field is so stretched in a multitude of domains and situations while no field excels actually. You can imagine how would have been if all the concentrated AI efforts were to be focused on health-care, fully automated hospitals and personal-care assistants & anti-virus development first. And only after that worked, to try to develop AI based sex-dolls, what a shame to all of us!

I feel myself uneasy now, regretting that I should have pursued what I started in the first place, AI medical informatics with agents that help fight addictions and the build of persuasive personal agents to help for a better healthy life of the individual. With the good AI.

In a hope that this crisis does not deepen and throw us in a new AI stone age we were just escaping, I expect that things will change, and a better evaluation of our AI priorities will be taken into consideration. Maybe a new AI authority will have to take the helm and supervise the further development.

C.Stefan – March 2020.

Job Breakthroughs

Startup vs. Larger Company:
Working for a smaller company is that you get to make more of an impact: Working in a larger corporation might have more benefits or a higher salary but a startup is where you can really make a difference and see the influence your work is having on the business. You’re heavily involved in each stage of production and your opinion is more likely to carry weight than at a larger, more structured operation. Decentralization of big companies would be done through tokenization. The shares will be done through ICOs.
Jobs in IT:
In Artificial Intelligence, the Internet of Things, data security, virtual reality and augmented reality, virtual worlds (and virtual assets) and bank-less, free nodes back-boned, Internet of payment. Jobs to see as or related to: big data engineer, Software 2.0 Engineer (maintain Neural Networks that write code), full-stack developer, security engineer, IoT architect and VR/AR engineer and hybrid engineers, with agile mindsets through the teams, with solid technology stacks knowledge that working together are able to bind different ends of the domain spectrum (similarly like DevOps is to the “from Code to Infrastructure” mindset paradigm), runners of decentralized Internet (sustained by Blockchain and other similar technologies yet to come, in order to back-up the Virtual Assets in the Virtual Worlds in the Decentralized Network).
Thus the skills needed to succeed in the IT jobs of tomorrow revolve around security certifications, programming and applications development, proficiency with cloud, decentralized architectures and mobile technologies, and other specialized skill sets giving also way to the hybrid IT roles that bind the business to IT.
Roles grow vertically based on business domain vs. technology stacks. For example: a Solutions Architect has the business domain knowledge but has also a technical background. He will develop complex technology solutions in a specific business domain. Software Architect knows in a deeper way the technology stacks. He will design the architecture of the technical implementation. Technical Lead is one with deeper knowledge of the, or a part of the technology stack. He designs using established patterns, coaches teams into the adopted technologies and unlocks teams in order to succeed in project delivery.
Data Scientists: it is essential for data scientists to work with languages like R, Python, SAS, Hadoop, Netezza in which they apply their knowledge in statistics, mathematics (algebra), matrices (multivariable) calculus. And to have a knowledge in platforms like MapReduce, GridGain, HPCC, Storm, Hive, Pig, Amazon S3.
The user as valuable “in the network” resource, in parallel digital universes (eg. Metaverse). Their actions should be monetized and generate income. We are producing valuable data even now by only navigating on FB, Google and other social networks which the system themselves uses it to become better (the long therm plan is building the future AI systems together). The “Internaut” will be one of the nicest job of the future.