Ethical AI vs Swarms of self replicating goo.
Ninjamoba LTD
Trusted social AI-assistant platform for Healthcare, Municipalities, and Education
Deep tech startups, such as those focused on AI, often face unique challenges in gaining traction and securing funding. These challenges stem from the nature of the industry, which often involves long sales cycles and the need for early proofs of concept. For deep tech startups to attract investment, it's essential to demonstrate early signs of market or customer interest. However, this can be difficult due to the typically long sales cycles until a multi-year contract is finally signed and recurring revenue can be booked. This process can take anywhere from 6 to 12 months and this is after a retail ready product has been developed[1].?
Venture capital (VC) bureaucracy can also pose challenges. There is substantial uncertainty and informational asymmetries surrounding the selection of new ventures, leading private investors to frequently make decisions based on soft information. This can also make it difficult for public officials to allocate capital to such companies through public funding[2].?
Moreover, securing funding from authorities can be a daunting task. Communities may face barriers to obtaining and effectively managing funding, especially those facing a financial crisis. The wide range of federal grant programs across many federal agencies can also create difficulties for communities attempting to obtain federal grants[3].
And here's the rub - there's not only a gap in deployment of Ai for social impact but there's a gap in funding how this AI can be researched and developed even before adoption and revenue can be manifested. So where does that leave other AI projects that aren't taking the high road?
In terms of internet traffic, it's estimated that 47% of it is generated by bots. These bots, which are becoming more advanced with the aid of AI and machine learning, are designed to mimic human behavior on websites or apps. They are often deployed by cybercriminals to carry out malicious activities such as spreading misinformation, conducting DDoS attacks, or inventory scraping[4].
The potential impact of self-directed AI on the internet is significant. If a self-directed AI reaches the internet, it could lead to swarms of self-replicating, self-directed conversational AI enabled for IOT. These AI could constantly pen test every port and every human access point, and every social media profile could be bombarded by "profiles" reaching out with various offers of work. They could even masquerade as familiar individuals after listening to and recording snippets of their voices[6].
Millions of fake personas have already been created by software piloted by humans for orchestrated nefarious political purposes. For instance, a bot-savvy supporter of author Chuck Wendig found that the controversy that led to Wendig's firing from Marvel was likely escalated by automated bots and anonymous accounts performing synthesized outrage[7].
Given these challenges and potential threats, it's crucial to invest in ethical AI development. Ethical AI can help meet these challenges, much like how addressing climate change requires concerted effort and investment. However, the decision to invest in ethical AI ultimately lies with stakeholders, including investors, governments, and the public. Centralized solutions beg the question - what happens if it goes rogue. We proposed decentralized human curated deployments that can be air gapped from the internet and function as "good enough" to address populations in health care and education on local networks. ensuring that you will always be in charge of the voice you hear on the other end of the phone.
Citations:
领英推荐
[12] https://www.dhirubhai.net/pulse/building-deep-tech-startups-challenges-opportunities-vinay-agastya